diff --git a/AutoMl/metadata/V1Beta1/Classification.php b/AutoMl/metadata/V1Beta1/Classification.php index f1db8847b3c2..412566a274ea 100644 --- a/AutoMl/metadata/V1Beta1/Classification.php +++ b/AutoMl/metadata/V1Beta1/Classification.php @@ -17,7 +17,7 @@ public static function initOnce() { \GPBMetadata\Google\Cloud\Automl\V1Beta1\Temporal::initOnce(); \GPBMetadata\Google\Api\Annotations::initOnce(); $pool->internalAddGeneratedFile(hex2bin( - "0a960c0a30676f6f676c652f636c6f75642f6175746f6d6c2f7631626574" . + "0aac0c0a30676f6f676c652f636c6f75642f6175746f6d6c2f7631626574" . "61312f636c617373696669636174696f6e2e70726f746f121b676f6f676c" . "652e636c6f75642e6175746f6d6c2e763162657461311a1c676f6f676c65" . "2f6170692f616e6e6f746174696f6e732e70726f746f22290a18436c6173" . @@ -28,7 +28,7 @@ public static function initOnce() { "2e676f6f676c652e636c6f75642e6175746f6d6c2e763162657461312e43" . "6c617373696669636174696f6e416e6e6f746174696f6e123e0a0c74696d" . "655f7365676d656e7418032001280b32282e676f6f676c652e636c6f7564" . - "2e6175746f6d6c2e763162657461312e54696d655365676d656e74229307" . + "2e6175746f6d6c2e763162657461312e54696d655365676d656e7422a907" . "0a1f436c617373696669636174696f6e4576616c756174696f6e4d657472" . "696373120e0a0661755f70726318012001280212170a0b626173655f6175" . "5f70726318022001280242021801120e0a0661755f726f63180620012802" . @@ -53,23 +53,23 @@ public static function initOnce() { "75655f706f7369746976655f636f756e74180a20012803121c0a1466616c" . "73655f706f7369746976655f636f756e74180b20012803121c0a1466616c" . "73655f6e656761746976655f636f756e74180c20012803121b0a13747275" . - "655f6e656761746976655f636f756e74180d200128031aaa010a0f436f6e" . + "655f6e656761746976655f636f756e74180d200128031ac0010a0f436f6e" . "667573696f6e4d6174726978121a0a12616e6e6f746174696f6e5f737065" . - "635f6964180120032809125d0a03726f7718022003280b32502e676f6f67" . - "6c652e636c6f75642e6175746f6d6c2e763162657461312e436c61737369" . - "6669636174696f6e4576616c756174696f6e4d6574726963732e436f6e66" . - "7573696f6e4d61747269782e526f771a1c0a03526f7712150a0d6578616d" . - "706c655f636f756e741801200328052a590a12436c617373696669636174" . - "696f6e5479706512230a1f434c415353494649434154494f4e5f54595045" . - "5f554e5350454349464945441000120e0a0a4d554c5449434c4153531001" . - "120e0a0a4d554c54494c4142454c100242b8010a1f636f6d2e676f6f676c" . - "652e636c6f75642e6175746f6d6c2e763162657461314213436c61737369" . - "6669636174696f6e50726f746f5a41676f6f676c652e676f6c616e672e6f" . - "72672f67656e70726f746f2f676f6f676c65617069732f636c6f75642f61" . - "75746f6d6c2f763162657461313b6175746f6d6cca021b476f6f676c655c" . - "436c6f75645c4175746f4d6c5c56316265746131ea021e476f6f676c653a" . - "3a436c6f75643a3a4175746f4d4c3a3a56316265746131620670726f746f" . - "33" + "635f696418012003280912140a0c646973706c61795f6e616d6518032003" . + "2809125d0a03726f7718022003280b32502e676f6f676c652e636c6f7564" . + "2e6175746f6d6c2e763162657461312e436c617373696669636174696f6e" . + "4576616c756174696f6e4d6574726963732e436f6e667573696f6e4d6174" . + "7269782e526f771a1c0a03526f7712150a0d6578616d706c655f636f756e" . + "741801200328052a590a12436c617373696669636174696f6e5479706512" . + "230a1f434c415353494649434154494f4e5f545950455f554e5350454349" . + "464945441000120e0a0a4d554c5449434c4153531001120e0a0a4d554c54" . + "494c4142454c100242b8010a1f636f6d2e676f6f676c652e636c6f75642e" . + "6175746f6d6c2e763162657461314213436c617373696669636174696f6e" . + "50726f746f5a41676f6f676c652e676f6c616e672e6f72672f67656e7072" . + "6f746f2f676f6f676c65617069732f636c6f75642f6175746f6d6c2f7631" . + "62657461313b6175746f6d6cca021b476f6f676c655c436c6f75645c4175" . + "746f4d6c5c56316265746131ea021e476f6f676c653a3a436c6f75643a3a" . + "4175746f4d4c3a3a56316265746131620670726f746f33" ), true); static::$is_initialized = true; diff --git a/AutoMl/metadata/V1Beta1/PredictionService.php b/AutoMl/metadata/V1Beta1/PredictionService.php index 0034825ffb39..6e8f5a3ab23a 100644 --- a/AutoMl/metadata/V1Beta1/PredictionService.php +++ b/AutoMl/metadata/V1Beta1/PredictionService.php @@ -22,7 +22,7 @@ public static function initOnce() { \GPBMetadata\Google\Longrunning\Operations::initOnce(); \GPBMetadata\Google\Api\Client::initOnce(); $pool->internalAddGeneratedFile(hex2bin( - "0ac60d0a34676f6f676c652f636c6f75642f6175746f6d6c2f7631626574" . + "0ac90e0a34676f6f676c652f636c6f75642f6175746f6d6c2f7631626574" . "61312f70726564696374696f6e5f736572766963652e70726f746f121b67" . "6f6f676c652e636c6f75642e6175746f6d6c2e763162657461311a34676f" . "6f676c652f636c6f75642f6175746f6d6c2f763162657461312f616e6e6f" . @@ -57,29 +57,34 @@ public static function initOnce() { "7318052003280b323c2e676f6f676c652e636c6f75642e6175746f6d6c2e" . "763162657461312e426174636850726564696374526571756573742e5061" . "72616d73456e7472791a2d0a0b506172616d73456e747279120b0a036b65" . - "79180120012809120d0a0576616c75651802200128093a02380122140a12" . - "426174636850726564696374526573756c7432b4030a1150726564696374" . - "696f6e5365727669636512a8010a0750726564696374122b2e676f6f676c" . - "652e636c6f75642e6175746f6d6c2e763162657461312e50726564696374" . - "526571756573741a2c2e676f6f676c652e636c6f75642e6175746f6d6c2e" . - "763162657461312e50726564696374526573706f6e7365224282d3e49302" . - "3c22372f763162657461312f7b6e616d653d70726f6a656374732f2a2f6c" . - "6f636174696f6e732f2a2f6d6f64656c732f2a7d3a707265646963743a01" . - "2a12a8010a0c42617463685072656469637412302e676f6f676c652e636c" . - "6f75642e6175746f6d6c2e763162657461312e4261746368507265646963" . - "74526571756573741a1d2e676f6f676c652e6c6f6e6772756e6e696e672e" . - "4f7065726174696f6e224782d3e4930241223c2f763162657461312f7b6e" . - "616d653d70726f6a656374732f2a2f6c6f636174696f6e732f2a2f6d6f64" . - "656c732f2a7d3a6261746368507265646963743a012a1a49ca4115617574" . - "6f6d6c2e676f6f676c65617069732e636f6dd2412e68747470733a2f2f77" . - "77772e676f6f676c65617069732e636f6d2f617574682f636c6f75642d70" . - "6c6174666f726d42bd010a1f636f6d2e676f6f676c652e636c6f75642e61" . - "75746f6d6c2e76316265746131421650726564696374696f6e5365727669" . - "636550726f746f50015a41676f6f676c652e676f6c616e672e6f72672f67" . - "656e70726f746f2f676f6f676c65617069732f636c6f75642f6175746f6d" . - "6c2f763162657461313b6175746f6d6cca021b476f6f676c655c436c6f75" . - "645c4175746f4d6c5c56316265746131ea021e476f6f676c653a3a436c6f" . - "75643a3a4175746f4d4c3a3a56316265746131620670726f746f33" + "79180120012809120d0a0576616c75651802200128093a0238012296010a" . + "12426174636850726564696374526573756c74124f0a086d657461646174" . + "6118012003280b323d2e676f6f676c652e636c6f75642e6175746f6d6c2e" . + "763162657461312e426174636850726564696374526573756c742e4d6574" . + "6164617461456e7472791a2f0a0d4d65746164617461456e747279120b0a" . + "036b6579180120012809120d0a0576616c75651802200128093a02380132" . + "b4030a1150726564696374696f6e5365727669636512a8010a0750726564" . + "696374122b2e676f6f676c652e636c6f75642e6175746f6d6c2e76316265" . + "7461312e50726564696374526571756573741a2c2e676f6f676c652e636c" . + "6f75642e6175746f6d6c2e763162657461312e5072656469637452657370" . + "6f6e7365224282d3e493023c22372f763162657461312f7b6e616d653d70" . + "726f6a656374732f2a2f6c6f636174696f6e732f2a2f6d6f64656c732f2a" . + "7d3a707265646963743a012a12a8010a0c42617463685072656469637412" . + "302e676f6f676c652e636c6f75642e6175746f6d6c2e763162657461312e" . + "426174636850726564696374526571756573741a1d2e676f6f676c652e6c" . + "6f6e6772756e6e696e672e4f7065726174696f6e224782d3e4930241223c" . + "2f763162657461312f7b6e616d653d70726f6a656374732f2a2f6c6f6361" . + "74696f6e732f2a2f6d6f64656c732f2a7d3a626174636850726564696374" . + "3a012a1a49ca41156175746f6d6c2e676f6f676c65617069732e636f6dd2" . + "412e68747470733a2f2f7777772e676f6f676c65617069732e636f6d2f61" . + "7574682f636c6f75642d706c6174666f726d42bd010a1f636f6d2e676f6f" . + "676c652e636c6f75642e6175746f6d6c2e76316265746131421650726564" . + "696374696f6e5365727669636550726f746f50015a41676f6f676c652e67" . + "6f6c616e672e6f72672f67656e70726f746f2f676f6f676c65617069732f" . + "636c6f75642f6175746f6d6c2f763162657461313b6175746f6d6cca021b" . + "476f6f676c655c436c6f75645c4175746f4d6c5c56316265746131ea021e" . + "476f6f676c653a3a436c6f75643a3a4175746f4d4c3a3a56316265746131" . + "620670726f746f33" ), true); static::$is_initialized = true; diff --git a/AutoMl/metadata/V1Beta1/TableSpec.php b/AutoMl/metadata/V1Beta1/TableSpec.php index d272919c6f6b..4283c5d254fe 100644 --- a/AutoMl/metadata/V1Beta1/TableSpec.php +++ b/AutoMl/metadata/V1Beta1/TableSpec.php @@ -17,22 +17,23 @@ public static function initOnce() { \GPBMetadata\Google\Cloud\Automl\V1Beta1\Io::initOnce(); \GPBMetadata\Google\Api\Annotations::initOnce(); $pool->internalAddGeneratedFile(hex2bin( - "0aca030a2c676f6f676c652f636c6f75642f6175746f6d6c2f7631626574" . + "0ae3030a2c676f6f676c652f636c6f75642f6175746f6d6c2f7631626574" . "61312f7461626c655f737065632e70726f746f121b676f6f676c652e636c" . "6f75642e6175746f6d6c2e763162657461311a1c676f6f676c652f617069" . - "2f616e6e6f746174696f6e732e70726f746f22ae010a095461626c655370" . + "2f616e6e6f746174696f6e732e70726f746f22c7010a095461626c655370" . "6563120c0a046e616d65180120012809121b0a1374696d655f636f6c756d" . "6e5f737065635f696418022001280912110a09726f775f636f756e741803" . - "2001280312140a0c636f6c756d6e5f636f756e74180720012803123f0a0d" . - "696e7075745f636f6e6669677318052003280b32282e676f6f676c652e63" . - "6c6f75642e6175746f6d6c2e763162657461312e496e707574436f6e6669" . - "67120c0a046574616718062001280942a5010a1f636f6d2e676f6f676c65" . - "2e636c6f75642e6175746f6d6c2e7631626574613150015a41676f6f676c" . - "652e676f6c616e672e6f72672f67656e70726f746f2f676f6f676c656170" . - "69732f636c6f75642f6175746f6d6c2f763162657461313b6175746f6d6c" . - "ca021b476f6f676c655c436c6f75645c4175746f4d6c5c56316265746131" . - "ea021e476f6f676c653a3a436c6f75643a3a4175746f4d4c3a3a56316265" . - "746131620670726f746f33" + "2001280312170a0f76616c69645f726f775f636f756e7418042001280312" . + "140a0c636f6c756d6e5f636f756e74180720012803123f0a0d696e707574" . + "5f636f6e6669677318052003280b32282e676f6f676c652e636c6f75642e" . + "6175746f6d6c2e763162657461312e496e707574436f6e666967120c0a04" . + "6574616718062001280942a5010a1f636f6d2e676f6f676c652e636c6f75" . + "642e6175746f6d6c2e7631626574613150015a41676f6f676c652e676f6c" . + "616e672e6f72672f67656e70726f746f2f676f6f676c65617069732f636c" . + "6f75642f6175746f6d6c2f763162657461313b6175746f6d6cca021b476f" . + "6f676c655c436c6f75645c4175746f4d6c5c56316265746131ea021e476f" . + "6f676c653a3a436c6f75643a3a4175746f4d4c3a3a563162657461316206" . + "70726f746f33" ), true); static::$is_initialized = true; diff --git a/AutoMl/metadata/V1Beta1/Tables.php b/AutoMl/metadata/V1Beta1/Tables.php index 0be900e568bc..ded269f5e034 100644 --- a/AutoMl/metadata/V1Beta1/Tables.php +++ b/AutoMl/metadata/V1Beta1/Tables.php @@ -24,7 +24,7 @@ public static function initOnce() { \GPBMetadata\Google\Protobuf\Timestamp::initOnce(); \GPBMetadata\Google\Api\Annotations::initOnce(); $pool->internalAddGeneratedFile(hex2bin( - "0ad50e0a28676f6f676c652f636c6f75642f6175746f6d6c2f7631626574" . + "0ac80d0a28676f6f676c652f636c6f75642f6175746f6d6c2f7631626574" . "61312f7461626c65732e70726f746f121b676f6f676c652e636c6f75642e" . "6175746f6d6c2e763162657461311a2d676f6f676c652f636c6f75642f61" . "75746f6d6c2f763162657461312f636f6c756d6e5f737065632e70726f74" . @@ -51,42 +51,37 @@ public static function initOnce() { "6172676574436f6c756d6e436f7272656c6174696f6e73456e747279120b" . "0a036b6579180120012809123c0a0576616c756518022001280b322d2e67" . "6f6f676c652e636c6f75642e6175746f6d6c2e763162657461312e436f72" . - "72656c6174696f6e53746174733a0238012296040a135461626c65734d6f" . + "72656c6174696f6e53746174733a0238012289030a135461626c65734d6f" . "64656c4d6574616461746112430a127461726765745f636f6c756d6e5f73" . "70656318022001280b32272e676f6f676c652e636c6f75642e6175746f6d" . "6c2e763162657461312e436f6c756d6e53706563124b0a1a696e7075745f" . "666561747572655f636f6c756d6e5f737065637318032003280b32272e67" . "6f6f676c652e636c6f75642e6175746f6d6c2e763162657461312e436f6c" . "756d6e53706563121e0a166f7074696d697a6174696f6e5f6f626a656374" . - "697665180420012809122d0a236f7074696d697a6174696f6e5f6f626a65" . - "63746976655f726563616c6c5f76616c7565181120012802480012300a26" . - "6f7074696d697a6174696f6e5f6f626a6563746976655f70726563697369" . - "6f6e5f76616c7565181220012802480012540a187461626c65735f6d6f64" . - "656c5f636f6c756d6e5f696e666f18052003280b32322e676f6f676c652e" . - "636c6f75642e6175746f6d6c2e763162657461312e5461626c65734d6f64" . - "656c436f6c756d6e496e666f12250a1d747261696e5f6275646765745f6d" . - "696c6c695f6e6f64655f686f75727318062001280312230a1b747261696e" . - "5f636f73745f6d696c6c695f6e6f64655f686f757273180720012803121e" . - "0a1664697361626c655f6561726c795f73746f7070696e67180c20012808" . - "422a0a286164646974696f6e616c5f6f7074696d697a6174696f6e5f6f62" . - "6a6563746976655f636f6e66696722e5010a105461626c6573416e6e6f74" . - "6174696f6e120d0a0573636f726518012001280212450a13707265646963" . - "74696f6e5f696e74657276616c18042001280b32282e676f6f676c652e63" . - "6c6f75642e6175746f6d6c2e763162657461312e446f75626c6552616e67" . - "6512250a0576616c756518022001280b32162e676f6f676c652e70726f74" . - "6f6275662e56616c756512540a187461626c65735f6d6f64656c5f636f6c" . - "756d6e5f696e666f18032003280b32322e676f6f676c652e636c6f75642e" . - "6175746f6d6c2e763162657461312e5461626c65734d6f64656c436f6c75" . - "6d6e496e666f226a0a155461626c65734d6f64656c436f6c756d6e496e66" . - "6f12180a10636f6c756d6e5f737065635f6e616d65180120012809121b0a" . - "13636f6c756d6e5f646973706c61795f6e616d65180220012809121a0a12" . - "666561747572655f696d706f7274616e636518032001280242a5010a1f63" . - "6f6d2e676f6f676c652e636c6f75642e6175746f6d6c2e76316265746131" . - "50015a41676f6f676c652e676f6c616e672e6f72672f67656e70726f746f" . - "2f676f6f676c65617069732f636c6f75642f6175746f6d6c2f7631626574" . - "61313b6175746f6d6cca021b476f6f676c655c436c6f75645c4175746f4d" . - "6c5c56316265746131ea021e476f6f676c653a3a436c6f75643a3a417574" . - "6f4d4c3a3a56316265746131620670726f746f33" + "69766518042001280912540a187461626c65735f6d6f64656c5f636f6c75" . + "6d6e5f696e666f18052003280b32322e676f6f676c652e636c6f75642e61" . + "75746f6d6c2e763162657461312e5461626c65734d6f64656c436f6c756d" . + "6e496e666f12250a1d747261696e5f6275646765745f6d696c6c695f6e6f" . + "64655f686f75727318062001280312230a1b747261696e5f636f73745f6d" . + "696c6c695f6e6f64655f686f757273180720012803121e0a166469736162" . + "6c655f6561726c795f73746f7070696e67180c2001280822e5010a105461" . + "626c6573416e6e6f746174696f6e120d0a0573636f726518012001280212" . + "450a1370726564696374696f6e5f696e74657276616c18042001280b3228" . + "2e676f6f676c652e636c6f75642e6175746f6d6c2e763162657461312e44" . + "6f75626c6552616e676512250a0576616c756518022001280b32162e676f" . + "6f676c652e70726f746f6275662e56616c756512540a187461626c65735f" . + "6d6f64656c5f636f6c756d6e5f696e666f18032003280b32322e676f6f67" . + "6c652e636c6f75642e6175746f6d6c2e763162657461312e5461626c6573" . + "4d6f64656c436f6c756d6e496e666f226a0a155461626c65734d6f64656c" . + "436f6c756d6e496e666f12180a10636f6c756d6e5f737065635f6e616d65" . + "180120012809121b0a13636f6c756d6e5f646973706c61795f6e616d6518" . + "0220012809121a0a12666561747572655f696d706f7274616e6365180320" . + "01280242a5010a1f636f6d2e676f6f676c652e636c6f75642e6175746f6d" . + "6c2e7631626574613150015a41676f6f676c652e676f6c616e672e6f7267" . + "2f67656e70726f746f2f676f6f676c65617069732f636c6f75642f617574" . + "6f6d6c2f763162657461313b6175746f6d6cca021b476f6f676c655c436c" . + "6f75645c4175746f4d6c5c56316265746131ea021e476f6f676c653a3a43" . + "6c6f75643a3a4175746f4d4c3a3a56316265746131620670726f746f33" ), true); static::$is_initialized = true; diff --git a/AutoMl/src/V1beta1/AutoMlGrpcClient.php b/AutoMl/src/V1beta1/AutoMlGrpcClient.php index 2d04aa860e01..b57c7253c6c2 100644 --- a/AutoMl/src/V1beta1/AutoMlGrpcClient.php +++ b/AutoMl/src/V1beta1/AutoMlGrpcClient.php @@ -328,8 +328,7 @@ public function DeleteModel(\Google\Cloud\AutoMl\V1beta1\DeleteModelRequest $arg * [node_number][google.cloud.automl.v1beta1.ImageObjectDetectionModelDeploymentMetadata.node_number]) * will reset the deployment state without pausing the model's availability. * - * Only applicable for Text Classification, Image Object Detection and Tables; - * all other domains manage deployment automatically. + * Only applicable for Text Classification, Image Object Detection and Tables; all other domains manage deployment automatically. * * Returns an empty response in the * [response][google.longrunning.Operation.response] field when it completes. diff --git a/AutoMl/src/V1beta1/BatchPredictInputConfig.php b/AutoMl/src/V1beta1/BatchPredictInputConfig.php index 60167cbfb6f5..2f9a6b787fd0 100644 --- a/AutoMl/src/V1beta1/BatchPredictInputConfig.php +++ b/AutoMl/src/V1beta1/BatchPredictInputConfig.php @@ -17,6 +17,26 @@ * The formats are represented in EBNF with commas being literal and with * non-terminal symbols defined near the end of this comment. The formats * are: + * * For Image Classification: + * CSV file(s) with each line having just a single column: + * GCS_FILE_PATH + * which leads to image of up to 30MB in size. Supported + * extensions: .JPEG, .GIF, .PNG. This path is treated as the ID in + * the Batch predict output. + * Three sample rows: + * gs://folder/image1.jpeg + * gs://folder/image2.gif + * gs://folder/image3.png + * * For Image Object Detection: + * CSV file(s) with each line having just a single column: + * GCS_FILE_PATH + * which leads to image of up to 30MB in size. Supported + * extensions: .JPEG, .GIF, .PNG. This path is treated as the ID in + * the Batch predict output. + * Three sample rows: + * gs://folder/image1.jpeg + * gs://folder/image2.gif + * gs://folder/image3.png * * For Video Classification: * CSV file(s) with each line in format: * GCS_FILE_PATH,TIME_SEGMENT_START,TIME_SEGMENT_END @@ -39,6 +59,26 @@ * gs://folder/video1.mp4,10,240 * gs://folder/video1.mp4,300,360 * gs://folder/vid2.mov,0,inf + * * For Text Classification: + * CSV file(s) with each line having just a single column: + * GCS_FILE_PATH | TEXT_SNIPPET + * Any given text file can have size upto 128kB. + * Any given text snippet content must have 60,000 characters or less. + * Three sample rows: + * gs://folder/text1.txt + * "Some text content to predict" + * gs://folder/text3.pdf + * Supported file extensions: .txt, .pdf + * * For Text Sentiment: + * CSV file(s) with each line having just a single column: + * GCS_FILE_PATH | TEXT_SNIPPET + * Any given text file can have size upto 128kB. + * Any given text snippet content must have 500 characters or less. + * Three sample rows: + * gs://folder/text1.txt + * "Some text content to predict" + * gs://folder/text3.pdf + * Supported file extensions: .txt, .pdf * * For Text Extraction * .JSONL (i.e. JSON Lines) file(s) which either provide text in-line or * as documents (for a single BatchPredict call only one of the these @@ -109,79 +149,40 @@ * 100GB or smaller, where first file must have a header containing * column names. If the first row of a subsequent file is the same as * the header, then it is also treated as a header. All other rows - * contain values for the corresponding columns. For all - * CLASSIFICATION and REGRESSION - * [prediction_type-s][google.cloud.automl.v1beta1.TablesModelMetadata.prediction_type]: - * The column names must contain the model's + * contain values for the corresponding columns. + * The column names must contain the model's * [input_feature_column_specs'][google.cloud.automl.v1beta1.TablesModelMetadata.input_feature_column_specs] * [display_name-s][google.cloud.automl.v1beta1.ColumnSpec.display_name] - * (order doesn't matter). The columns corresponding to the model's - * input feature column specs must contain values compatible with - * the column spec's data types. Prediction on all the rows, i.e. - * the CSV lines, will be attempted. First three sample rows of a - * CSV file: + * (order doesn't matter). The columns corresponding to the model's + * input feature column specs must contain values compatible with the + * column spec's data types. Prediction on all the rows, i.e. the CSV + * lines, will be attempted. For FORECASTING + * [prediction_type][google.cloud.automl.v1beta1.TablesModelMetadata.prediction_type]: + * all columns having + * [TIME_SERIES_AVAILABLE_PAST_ONLY][google.cloud.automl.v1beta1.ColumnSpec.ForecastingMetadata.ColumnType] + * type will be ignored. + * First three sample rows of a CSV file: * "First Name","Last Name","Dob","Addresses" * "John","Doe","1968-01-22","[{"status":"current","address":"123_First_Avenue","city":"Seattle","state":"WA","zip":"11111","numberOfYears":"1"},{"status":"previous","address":"456_Main_Street","city":"Portland","state":"OR","zip":"22222","numberOfYears":"5"}]" * "Jane","Doe","1980-10-16","[{"status":"current","address":"789_Any_Avenue","city":"Albany","state":"NY","zip":"33333","numberOfYears":"2"},{"status":"previous","address":"321_Main_Street","city":"Hoboken","state":"NJ","zip":"44444","numberOfYears":"3"}]} - * For FORECASTING - * [prediction_type][google.cloud.automl.v1beta1.TablesModelMetadata.prediction_type]: - * The column names must contain the union of the model's - * [input_feature_column_specs'][google.cloud.automl.v1beta1.TablesModelMetadata.input_feature_column_specs] - * [display_name-s][google.cloud.automl.v1beta1.ColumnSpec.display_name] - * and - * [target_column_specs'][google.cloud.automl.v1beta1.TablesModelMetadata.target_column_spec] - * [display_name][google.cloud.automl.v1beta1.ColumnSpec.display_name] - * (order doesn't matter), with values compatible with these column - * specs data types, except as specified below. - * The input rows must contain not only the to-be-predicted rows - * but also the historical data rows, even if they would be - * identical as the ones on which the model has been trained. - * The historical rows must have non-NULL target column - * values. The to-be-predicted rows must have NULL values in the - * target column and all columns having - * [TIME_SERIES_AVAILABLE_PAST_ONLY][google.cloud.automl.v1beta1.ColumnSpec.ForecastingMetadata.ColumnType.KEY] - * type, regardless if these columns are - * [nullable][google.cloud.automl.v1beta1.DataType.nullable]. - * Prediction only on the to-be-predicted rows will be attempted. - * First four sample rows of a CSV file: - * "Year","City","OlympicsThatYear","Population","WaterUsedGigaGallons" - * "2000","NYC","true","8008278","452.7" - * "2001","NYC","false","8024963","432.2" - * "2002","NYC","true","","" * BigQuery case: * An URI of a BigQuery table. The user data size of the BigQuery * table must be 100GB or smaller. - * For all CLASSIFICATION and REGRESSION - * [prediction_type-s][google.cloud.automl.v1beta1.TablesModelMetadata.prediction_type]: - * The column names must contain the model's + * The column names must contain the model's * [input_feature_column_specs'][google.cloud.automl.v1beta1.TablesModelMetadata.input_feature_column_specs] * [display_name-s][google.cloud.automl.v1beta1.ColumnSpec.display_name] - * (order doesn't matter). The columns corresponding to the model's - * input feature column specs must contain values compatible with - * the column spec's data types. Prediction on all the rows of the - * table will be attempted. - * For FORECASTING + * (order doesn't matter). The columns corresponding to the model's + * input feature column specs must contain values compatible with the + * column spec's data types. Prediction on all the rows of the table + * will be attempted. For FORECASTING * [prediction_type][google.cloud.automl.v1beta1.TablesModelMetadata.prediction_type]: - * The column names must contain the union of the model's - * [input_feature_column_specs'][google.cloud.automl.v1beta1.TablesModelMetadata.input_feature_column_specs] - * [display_name-s][google.cloud.automl.v1beta1.ColumnSpec.display_name] - * and - * [target_column_specs'][google.cloud.automl.v1beta1.TablesModelMetadata.target_column_spec] - * [display_name][google.cloud.automl.v1beta1.ColumnSpec.display_name] - * (order doesn't matter), with values compatible with these column - * specs data types, except as specified below. - * The table's rows must contain not only the to-be-predicted rows - * but also the historical data rows, even if they would be - * identical as the ones on which the model has been trained. - * The historical rows must have non-NULL target column values. - * The to-be-predicted rows must have NULL values in the - * target column and all columns having - * [TIME_SERIES_AVAILABLE_PAST_ONLY][google.cloud.automl.v1beta1.ColumnSpec.ForecastingMetadata.ColumnType.KEY] - * type, regardless if these columns are - * [nullable][google.cloud.automl.v1beta1.DataType.nullable]. - * Prediction only on the to-be-predicted rows will be attempted. + * all columns having + * [TIME_SERIES_AVAILABLE_PAST_ONLY][google.cloud.automl.v1beta1.ColumnSpec.ForecastingMetadata.ColumnType] + * type will be ignored. * Definitions: * GCS_FILE_PATH = A path to file on GCS, e.g. "gs://folder/video.avi". + * TEXT_SNIPPET = A content of a text snippet, UTF-8 encoded, enclosed within + * double quotes ("") * TIME_SEGMENT_START = TIME_OFFSET * Expresses a beginning, inclusive, of a time segment * within an diff --git a/AutoMl/src/V1beta1/BatchPredictOutputConfig.php b/AutoMl/src/V1beta1/BatchPredictOutputConfig.php index f28432040daf..bc876627d1dd 100644 --- a/AutoMl/src/V1beta1/BatchPredictOutputConfig.php +++ b/AutoMl/src/V1beta1/BatchPredictOutputConfig.php @@ -13,11 +13,51 @@ * As destination the * [gcs_destination][google.cloud.automl.v1beta1.BatchPredictOutputConfig.gcs_destination] * must be set unless specified otherwise for a domain. If gcs_destination is - * set then in the given directory a new directory will be created. Its name + * set then in the given directory a new directory is created. Its name * will be * "prediction--", * where timestamp is in YYYY-MM-DDThh:mm:ss.sssZ ISO-8601 format. The contents * of it depends on the ML problem the predictions are made for. + * * For Image Classification: + * In the created directory files `image_classification_1.jsonl`, + * `image_classification_2.jsonl`,...,`image_classification_N.jsonl` + * will be created, where N may be 1, and depends on the + * total number of the successfully predicted images and annotations. + * A single image will be listed only once with all its annotations, + * and its annotations will never be split across files. + * Each .JSONL file will contain, per line, a JSON representation of a + * proto that wraps image's "ID" : "" followed by a list of + * zero or more AnnotationPayload protos (called annotations), which + * have classification detail populated. + * If prediction for any image failed (partially or completely), then an + * additional `errors_1.jsonl`, `errors_2.jsonl`,..., `errors_N.jsonl` + * files will be created (N depends on total number of failed + * predictions). These files will have a JSON representation of a proto + * that wraps the same "ID" : "" but here followed by + * exactly one + * [`google.rpc.Status`](https: + * //github.com/googleapis/googleapis/blob/master/google/rpc/status.proto) + * containing only `code` and `message`fields. + * * For Image Object Detection: + * In the created directory files `image_object_detection_1.jsonl`, + * `image_object_detection_2.jsonl`,...,`image_object_detection_N.jsonl` + * will be created, where N may be 1, and depends on the + * total number of the successfully predicted images and annotations. + * Each .JSONL file will contain, per line, a JSON representation of a + * proto that wraps image's "ID" : "" followed by a list of + * zero or more AnnotationPayload protos (called annotations), which + * have image_object_detection detail populated. A single image will + * be listed only once with all its annotations, and its annotations + * will never be split across files. + * If prediction for any image failed (partially or completely), then + * additional `errors_1.jsonl`, `errors_2.jsonl`,..., `errors_N.jsonl` + * files will be created (N depends on total number of failed + * predictions). These files will have a JSON representation of a proto + * that wraps the same "ID" : "" but here followed by + * exactly one + * [`google.rpc.Status`](https: + * //github.com/googleapis/googleapis/blob/master/google/rpc/status.proto) + * containing only `code` and `message`fields. * * For Video Classification: * In the created directory a video_classification.csv file, and a .JSON * file per each video classification requested in the input (i.e. each @@ -63,6 +103,46 @@ * for each frame of the video time segment the file is assigned to in * video_object_tracking.csv. All AnnotationPayload protos will have * video_object_tracking field set. + * * For Text Classification: + * In the created directory files `text_classification_1.jsonl`, + * `text_classification_2.jsonl`,...,`text_classification_N.jsonl` + * will be created, where N may be 1, and depends on the + * total number of inputs and annotations found. + * Each .JSONL file will contain, per line, a JSON representation of a + * proto that wraps input text snippet or input text file and a list of + * zero or more AnnotationPayload protos (called annotations), which + * have classification detail populated. A single text snippet or file + * will be listed only once with all its annotations, and its + * annotations will never be split across files. + * If prediction for any text snippet or file failed (partially or + * completely), then additional `errors_1.jsonl`, `errors_2.jsonl`,..., + * `errors_N.jsonl` files will be created (N depends on total number of + * failed predictions). These files will have a JSON representation of a + * proto that wraps input text snippet or input text file followed by + * exactly one + * [`google.rpc.Status`](https: + * //github.com/googleapis/googleapis/blob/master/google/rpc/status.proto) + * containing only `code` and `message`. + * * For Text Sentiment: + * In the created directory files `text_sentiment_1.jsonl`, + * `text_sentiment_2.jsonl`,...,`text_sentiment_N.jsonl` + * will be created, where N may be 1, and depends on the + * total number of inputs and annotations found. + * Each .JSONL file will contain, per line, a JSON representation of a + * proto that wraps input text snippet or input text file and a list of + * zero or more AnnotationPayload protos (called annotations), which + * have text_sentiment detail populated. A single text snippet or file + * will be listed only once with all its annotations, and its + * annotations will never be split across files. + * If prediction for any text snippet or file failed (partially or + * completely), then additional `errors_1.jsonl`, `errors_2.jsonl`,..., + * `errors_N.jsonl` files will be created (N depends on total number of + * failed predictions). These files will have a JSON representation of a + * proto that wraps input text snippet or input text file followed by + * exactly one + * [`google.rpc.Status`](https: + * //github.com/googleapis/googleapis/blob/master/google/rpc/status.proto) + * containing only `code` and `message`. * * For Text Extraction: * In the created directory files `text_extraction_1.jsonl`, * `text_extraction_2.jsonl`,...,`text_extraction_N.jsonl` @@ -72,7 +152,8 @@ * used inline text, or documents. * If input was inline, then each .JSONL file will contain, per line, * a JSON representation of a proto that wraps given in request text - * snippet's "id" : "" followed by a list of zero or more + * snippet's "id" (if specified), followed by input text snippet, + * and a list of zero or more * AnnotationPayload protos (called annotations), which have * text_extraction detail populated. A single text snippet will be * listed only once with all its annotations, and its annotations will diff --git a/AutoMl/src/V1beta1/BatchPredictRequest.php b/AutoMl/src/V1beta1/BatchPredictRequest.php index 1085050c6bb4..ac52bdf590a8 100644 --- a/AutoMl/src/V1beta1/BatchPredictRequest.php +++ b/AutoMl/src/V1beta1/BatchPredictRequest.php @@ -37,6 +37,21 @@ class BatchPredictRequest extends \Google\Protobuf\Internal\Message /** * Additional domain-specific parameters for the predictions, any string must * be up to 25000 characters long. + * * For Text Classification: + * `score_threshold` - (float) A value from 0.0 to 1.0. When the model + * makes predictions for a text snippet, it will only produce results + * that have at least this confidence score. The default is 0.5. + * * For Image Classification: + * `score_threshold` - (float) A value from 0.0 to 1.0. When the model + * makes predictions for an image, it will only produce results that + * have at least this confidence score. The default is 0.5. + * * For Image Object Detection: + * `score_threshold` - (float) When Model detects objects on the image, + * it will only produce bounding boxes which have at least this + * confidence score. Value in 0 to 1 range, default is 0.5. + * `max_bounding_box_count` - (int64) No more than this number of bounding + * boxes will be produced per image. Default is 100, the + * requested value may be limited by server. * * For Video Classification : * `score_threshold` - (float) A value from 0.0 to 1.0. When the model * makes predictions for a video, it will only produce results that @@ -95,6 +110,21 @@ class BatchPredictRequest extends \Google\Protobuf\Internal\Message * @type array|\Google\Protobuf\Internal\MapField $params * Additional domain-specific parameters for the predictions, any string must * be up to 25000 characters long. + * * For Text Classification: + * `score_threshold` - (float) A value from 0.0 to 1.0. When the model + * makes predictions for a text snippet, it will only produce results + * that have at least this confidence score. The default is 0.5. + * * For Image Classification: + * `score_threshold` - (float) A value from 0.0 to 1.0. When the model + * makes predictions for an image, it will only produce results that + * have at least this confidence score. The default is 0.5. + * * For Image Object Detection: + * `score_threshold` - (float) When Model detects objects on the image, + * it will only produce bounding boxes which have at least this + * confidence score. Value in 0 to 1 range, default is 0.5. + * `max_bounding_box_count` - (int64) No more than this number of bounding + * boxes will be produced per image. Default is 100, the + * requested value may be limited by server. * * For Video Classification : * `score_threshold` - (float) A value from 0.0 to 1.0. When the model * makes predictions for a video, it will only produce results that @@ -222,6 +252,21 @@ public function setOutputConfig($var) /** * Additional domain-specific parameters for the predictions, any string must * be up to 25000 characters long. + * * For Text Classification: + * `score_threshold` - (float) A value from 0.0 to 1.0. When the model + * makes predictions for a text snippet, it will only produce results + * that have at least this confidence score. The default is 0.5. + * * For Image Classification: + * `score_threshold` - (float) A value from 0.0 to 1.0. When the model + * makes predictions for an image, it will only produce results that + * have at least this confidence score. The default is 0.5. + * * For Image Object Detection: + * `score_threshold` - (float) When Model detects objects on the image, + * it will only produce bounding boxes which have at least this + * confidence score. Value in 0 to 1 range, default is 0.5. + * `max_bounding_box_count` - (int64) No more than this number of bounding + * boxes will be produced per image. Default is 100, the + * requested value may be limited by server. * * For Video Classification : * `score_threshold` - (float) A value from 0.0 to 1.0. When the model * makes predictions for a video, it will only produce results that @@ -271,6 +316,21 @@ public function getParams() /** * Additional domain-specific parameters for the predictions, any string must * be up to 25000 characters long. + * * For Text Classification: + * `score_threshold` - (float) A value from 0.0 to 1.0. When the model + * makes predictions for a text snippet, it will only produce results + * that have at least this confidence score. The default is 0.5. + * * For Image Classification: + * `score_threshold` - (float) A value from 0.0 to 1.0. When the model + * makes predictions for an image, it will only produce results that + * have at least this confidence score. The default is 0.5. + * * For Image Object Detection: + * `score_threshold` - (float) When Model detects objects on the image, + * it will only produce bounding boxes which have at least this + * confidence score. Value in 0 to 1 range, default is 0.5. + * `max_bounding_box_count` - (int64) No more than this number of bounding + * boxes will be produced per image. Default is 100, the + * requested value may be limited by server. * * For Video Classification : * `score_threshold` - (float) A value from 0.0 to 1.0. When the model * makes predictions for a video, it will only produce results that diff --git a/AutoMl/src/V1beta1/BatchPredictResult.php b/AutoMl/src/V1beta1/BatchPredictResult.php index dc2024670500..db80ec7e0537 100644 --- a/AutoMl/src/V1beta1/BatchPredictResult.php +++ b/AutoMl/src/V1beta1/BatchPredictResult.php @@ -17,6 +17,18 @@ */ class BatchPredictResult extends \Google\Protobuf\Internal\Message { + /** + * Additional domain-specific prediction response metadata. + * * For Image Object Detection: + * `max_bounding_box_count` - (int64) At most that many bounding boxes per + * image could have been returned. + * * For Video Object Tracking: + * `max_bounding_box_count` - (int64) At most that many bounding boxes per + * frame could have been returned. + * + * Generated from protobuf field map metadata = 1; + */ + private $metadata; /** * Constructor. @@ -24,6 +36,14 @@ class BatchPredictResult extends \Google\Protobuf\Internal\Message * @param array $data { * Optional. Data for populating the Message object. * + * @type array|\Google\Protobuf\Internal\MapField $metadata + * Additional domain-specific prediction response metadata. + * * For Image Object Detection: + * `max_bounding_box_count` - (int64) At most that many bounding boxes per + * image could have been returned. + * * For Video Object Tracking: + * `max_bounding_box_count` - (int64) At most that many bounding boxes per + * frame could have been returned. * } */ public function __construct($data = NULL) { @@ -31,5 +51,43 @@ public function __construct($data = NULL) { parent::__construct($data); } + /** + * Additional domain-specific prediction response metadata. + * * For Image Object Detection: + * `max_bounding_box_count` - (int64) At most that many bounding boxes per + * image could have been returned. + * * For Video Object Tracking: + * `max_bounding_box_count` - (int64) At most that many bounding boxes per + * frame could have been returned. + * + * Generated from protobuf field map metadata = 1; + * @return \Google\Protobuf\Internal\MapField + */ + public function getMetadata() + { + return $this->metadata; + } + + /** + * Additional domain-specific prediction response metadata. + * * For Image Object Detection: + * `max_bounding_box_count` - (int64) At most that many bounding boxes per + * image could have been returned. + * * For Video Object Tracking: + * `max_bounding_box_count` - (int64) At most that many bounding boxes per + * frame could have been returned. + * + * Generated from protobuf field map metadata = 1; + * @param array|\Google\Protobuf\Internal\MapField $var + * @return $this + */ + public function setMetadata($var) + { + $arr = GPBUtil::checkMapField($var, \Google\Protobuf\Internal\GPBType::STRING, \Google\Protobuf\Internal\GPBType::STRING); + $this->metadata = $arr; + + return $this; + } + } diff --git a/AutoMl/src/V1beta1/ClassificationEvaluationMetrics/ConfusionMatrix.php b/AutoMl/src/V1beta1/ClassificationEvaluationMetrics/ConfusionMatrix.php index d94584851250..934524c5b145 100644 --- a/AutoMl/src/V1beta1/ClassificationEvaluationMetrics/ConfusionMatrix.php +++ b/AutoMl/src/V1beta1/ClassificationEvaluationMetrics/ConfusionMatrix.php @@ -24,6 +24,17 @@ class ConfusionMatrix extends \Google\Protobuf\Internal\Message * Generated from protobuf field repeated string annotation_spec_id = 1; */ private $annotation_spec_id; + /** + * Output only. Display name of the annotation specs used in the confusion + * matrix, as they were at the moment of the evaluation. For Tables + * CLASSIFICATION + * [prediction_type-s][google.cloud.automl.v1beta1.TablesModelMetadata.prediction_type], + * distinct values of the target column at the moment of the model + * evaluation are populated here. + * + * Generated from protobuf field repeated string display_name = 3; + */ + private $display_name; /** * Output only. Rows in the confusion matrix. The number of rows is equal to * the size of `annotation_spec_id`. @@ -46,6 +57,13 @@ class ConfusionMatrix extends \Google\Protobuf\Internal\Message * For Tables CLASSIFICATION * [prediction_type][google.cloud.automl.v1beta1.TablesModelMetadata.prediction_type] * only list of [annotation_spec_display_name-s][] is populated. + * @type string[]|\Google\Protobuf\Internal\RepeatedField $display_name + * Output only. Display name of the annotation specs used in the confusion + * matrix, as they were at the moment of the evaluation. For Tables + * CLASSIFICATION + * [prediction_type-s][google.cloud.automl.v1beta1.TablesModelMetadata.prediction_type], + * distinct values of the target column at the moment of the model + * evaluation are populated here. * @type \Google\Cloud\AutoMl\V1beta1\ClassificationEvaluationMetrics\ConfusionMatrix\Row[]|\Google\Protobuf\Internal\RepeatedField $row * Output only. Rows in the confusion matrix. The number of rows is equal to * the size of `annotation_spec_id`. @@ -91,6 +109,42 @@ public function setAnnotationSpecId($var) return $this; } + /** + * Output only. Display name of the annotation specs used in the confusion + * matrix, as they were at the moment of the evaluation. For Tables + * CLASSIFICATION + * [prediction_type-s][google.cloud.automl.v1beta1.TablesModelMetadata.prediction_type], + * distinct values of the target column at the moment of the model + * evaluation are populated here. + * + * Generated from protobuf field repeated string display_name = 3; + * @return \Google\Protobuf\Internal\RepeatedField + */ + public function getDisplayName() + { + return $this->display_name; + } + + /** + * Output only. Display name of the annotation specs used in the confusion + * matrix, as they were at the moment of the evaluation. For Tables + * CLASSIFICATION + * [prediction_type-s][google.cloud.automl.v1beta1.TablesModelMetadata.prediction_type], + * distinct values of the target column at the moment of the model + * evaluation are populated here. + * + * Generated from protobuf field repeated string display_name = 3; + * @param string[]|\Google\Protobuf\Internal\RepeatedField $var + * @return $this + */ + public function setDisplayName($var) + { + $arr = GPBUtil::checkRepeatedField($var, \Google\Protobuf\Internal\GPBType::STRING); + $this->display_name = $arr; + + return $this; + } + /** * Output only. Rows in the confusion matrix. The number of rows is equal to * the size of `annotation_spec_id`. diff --git a/AutoMl/src/V1beta1/ColumnSpec.php b/AutoMl/src/V1beta1/ColumnSpec.php index fc56ae466fe8..3fc1605863b5 100644 --- a/AutoMl/src/V1beta1/ColumnSpec.php +++ b/AutoMl/src/V1beta1/ColumnSpec.php @@ -51,12 +51,7 @@ class ColumnSpec extends \Google\Protobuf\Internal\Message */ private $data_stats = null; /** - * Output only. Top 10 most correlated with this column columns of the table, - * ordered by - * [cramers_v][google.cloud.automl.v1beta1.CorrelationStats.cramers_v] metric. - * This field may be stale, see the ancestor's - * Dataset.tables_dataset_metadata.stats_update_time field - * for the timestamp at which these stats were last updated. + * Deprecated. * * Generated from protobuf field repeated .google.cloud.automl.v1beta1.ColumnSpec.CorrelatedColumn top_correlated_columns = 5; */ @@ -92,12 +87,7 @@ class ColumnSpec extends \Google\Protobuf\Internal\Message * Dataset.tables_dataset_metadata.stats_update_time field * for the timestamp at which these stats were last updated. * @type \Google\Cloud\AutoMl\V1beta1\ColumnSpec\CorrelatedColumn[]|\Google\Protobuf\Internal\RepeatedField $top_correlated_columns - * Output only. Top 10 most correlated with this column columns of the table, - * ordered by - * [cramers_v][google.cloud.automl.v1beta1.CorrelationStats.cramers_v] metric. - * This field may be stale, see the ancestor's - * Dataset.tables_dataset_metadata.stats_update_time field - * for the timestamp at which these stats were last updated. + * Deprecated. * @type string $etag * Used to perform consistent read-modify-write updates. If not set, a blind * "overwrite" update happens. @@ -229,12 +219,7 @@ public function setDataStats($var) } /** - * Output only. Top 10 most correlated with this column columns of the table, - * ordered by - * [cramers_v][google.cloud.automl.v1beta1.CorrelationStats.cramers_v] metric. - * This field may be stale, see the ancestor's - * Dataset.tables_dataset_metadata.stats_update_time field - * for the timestamp at which these stats were last updated. + * Deprecated. * * Generated from protobuf field repeated .google.cloud.automl.v1beta1.ColumnSpec.CorrelatedColumn top_correlated_columns = 5; * @return \Google\Protobuf\Internal\RepeatedField @@ -245,12 +230,7 @@ public function getTopCorrelatedColumns() } /** - * Output only. Top 10 most correlated with this column columns of the table, - * ordered by - * [cramers_v][google.cloud.automl.v1beta1.CorrelationStats.cramers_v] metric. - * This field may be stale, see the ancestor's - * Dataset.tables_dataset_metadata.stats_update_time field - * for the timestamp at which these stats were last updated. + * Deprecated. * * Generated from protobuf field repeated .google.cloud.automl.v1beta1.ColumnSpec.CorrelatedColumn top_correlated_columns = 5; * @param \Google\Cloud\AutoMl\V1beta1\ColumnSpec\CorrelatedColumn[]|\Google\Protobuf\Internal\RepeatedField $var diff --git a/AutoMl/src/V1beta1/Gapic/AutoMlGapicClient.php b/AutoMl/src/V1beta1/Gapic/AutoMlGapicClient.php index 4b7d29e67107..da48e0594076 100644 --- a/AutoMl/src/V1beta1/Gapic/AutoMlGapicClient.php +++ b/AutoMl/src/V1beta1/Gapic/AutoMlGapicClient.php @@ -621,12 +621,7 @@ public function createDataset($parent, $dataset, array $optionalArgs = []) * Optional. * * @type FieldMask $updateMask - * The update mask applies to the resource. For the `FieldMask` definition, - * see - * - * https: - * //developers.google.com/protocol-buffers - * // /docs/reference/google.protobuf#fieldmask + * The update mask applies to the resource. * @type RetrySettings|array $retrySettings * Retry settings to use for this call. Can be a * {@see Google\ApiCore\RetrySettings} object, or an associative array @@ -1369,8 +1364,7 @@ public function deleteModel($name, array $optionalArgs = []) * [node_number][google.cloud.automl.v1beta1.ImageObjectDetectionModelDeploymentMetadata.node_number]) * will reset the deployment state without pausing the model's availability. * - * Only applicable for Text Classification, Image Object Detection and Tables; - * all other domains manage deployment automatically. + * Only applicable for Text Classification, Image Object Detection and Tables; all other domains manage deployment automatically. * * Returns an empty response in the * [response][google.longrunning.Operation.response] field when it completes. @@ -2075,12 +2069,7 @@ public function listTableSpecs($parent, array $optionalArgs = []) * Optional. * * @type FieldMask $updateMask - * The update mask applies to the resource. For the `FieldMask` definition, - * see - * - * https: - * //developers.google.com/protocol-buffers - * // /docs/reference/google.protobuf#fieldmask + * The update mask applies to the resource. * @type RetrySettings|array $retrySettings * Retry settings to use for this call. Can be a * {@see Google\ApiCore\RetrySettings} object, or an associative array @@ -2280,12 +2269,7 @@ public function listColumnSpecs($parent, array $optionalArgs = []) * Optional. * * @type FieldMask $updateMask - * The update mask applies to the resource. For the `FieldMask` definition, - * see - * - * https: - * //developers.google.com/protocol-buffers - * // /docs/reference/google.protobuf#fieldmask + * The update mask applies to the resource. * @type RetrySettings|array $retrySettings * Retry settings to use for this call. Can be a * {@see Google\ApiCore\RetrySettings} object, or an associative array diff --git a/AutoMl/src/V1beta1/Gapic/PredictionServiceGapicClient.php b/AutoMl/src/V1beta1/Gapic/PredictionServiceGapicClient.php index 15a4711d3fa6..49cfb7da06af 100644 --- a/AutoMl/src/V1beta1/Gapic/PredictionServiceGapicClient.php +++ b/AutoMl/src/V1beta1/Gapic/PredictionServiceGapicClient.php @@ -323,6 +323,8 @@ public function __construct(array $options = []) * up to 5MB. Not available for FORECASTING. * * [prediction_type][google.cloud.automl.v1beta1.TablesModelMetadata.prediction_type]. + * * Text Sentiment - TextSnippet, content up 500 characters, UTF-8 + * encoded. * * Sample code: * ``` @@ -337,8 +339,7 @@ public function __construct(array $options = []) * ``` * * @param string $name Name of the model requested to serve the prediction. - * @param ExamplePayload $payload Required. - * Payload to perform a prediction on. The payload must match the + * @param ExamplePayload $payload Required. Payload to perform a prediction on. The payload must match the * problem type that the model was trained to solve. * @param array $optionalArgs { * Optional. @@ -352,6 +353,14 @@ public function __construct(array $options = []) * `score_threshold` - (float) A value from 0.0 to 1.0. When the model * makes predictions for an image, it will only produce results that have * at least this confidence score. The default is 0.5. + * + * * For Image Object Detection: + * `score_threshold` - (float) When Model detects objects on the image, + * it will only produce bounding boxes which have at least this + * confidence score. Value in 0 to 1 range, default is 0.5. + * `max_bounding_box_count` - (int64) No more than this number of bounding + * boxes will be returned in the response. Default is 100, the + * requested value may be limited by server. * * For Tables: * `feature_importance` - (boolean) Whether * @@ -404,9 +413,10 @@ public function predict($name, $payload, array $optionalArgs = []) * method. Once the operation is done, [BatchPredictResult][google.cloud.automl.v1beta1.BatchPredictResult] is returned in * the [response][google.longrunning.Operation.response] field. * Available for following ML problems: + * * Image Classification + * * Image Object Detection * * Video Classification - * * Video Object Tracking - * * Text Extraction + * * Video Object Tracking * Text Extraction * * Tables. * * Sample code: @@ -461,6 +471,27 @@ public function predict($name, $payload, array $optionalArgs = []) * Additional domain-specific parameters for the predictions, any string must * be up to 25000 characters long. * + * * For Text Classification: + * + * `score_threshold` - (float) A value from 0.0 to 1.0. When the model + * makes predictions for a text snippet, it will only produce results + * that have at least this confidence score. The default is 0.5. + * + * * For Image Classification: + * + * `score_threshold` - (float) A value from 0.0 to 1.0. When the model + * makes predictions for an image, it will only produce results that + * have at least this confidence score. The default is 0.5. + * + * * For Image Object Detection: + * + * `score_threshold` - (float) When Model detects objects on the image, + * it will only produce bounding boxes which have at least this + * confidence score. Value in 0 to 1 range, default is 0.5. + * `max_bounding_box_count` - (int64) No more than this number of bounding + * boxes will be produced per image. Default is 100, the + * requested value may be limited by server. + * * * For Video Classification : * `score_threshold` - (float) A value from 0.0 to 1.0. When the model * makes predictions for a video, it will only produce results that diff --git a/AutoMl/src/V1beta1/ImageObjectDetectionAnnotation.php b/AutoMl/src/V1beta1/ImageObjectDetectionAnnotation.php index bdf092b96a8f..a1c215e5dc93 100644 --- a/AutoMl/src/V1beta1/ImageObjectDetectionAnnotation.php +++ b/AutoMl/src/V1beta1/ImageObjectDetectionAnnotation.php @@ -16,15 +16,13 @@ class ImageObjectDetectionAnnotation extends \Google\Protobuf\Internal\Message { /** - * Output only. - * The rectangle representing the object location. + * Output only. The rectangle representing the object location. * * Generated from protobuf field .google.cloud.automl.v1beta1.BoundingPoly bounding_box = 1; */ private $bounding_box = null; /** - * Output only. - * The confidence that this annotation is positive for the parent example, + * Output only. The confidence that this annotation is positive for the parent example, * value in [0, 1], higher means higher positivity confidence. * * Generated from protobuf field float score = 2; @@ -38,11 +36,9 @@ class ImageObjectDetectionAnnotation extends \Google\Protobuf\Internal\Message * Optional. Data for populating the Message object. * * @type \Google\Cloud\AutoMl\V1beta1\BoundingPoly $bounding_box - * Output only. - * The rectangle representing the object location. + * Output only. The rectangle representing the object location. * @type float $score - * Output only. - * The confidence that this annotation is positive for the parent example, + * Output only. The confidence that this annotation is positive for the parent example, * value in [0, 1], higher means higher positivity confidence. * } */ @@ -52,8 +48,7 @@ public function __construct($data = NULL) { } /** - * Output only. - * The rectangle representing the object location. + * Output only. The rectangle representing the object location. * * Generated from protobuf field .google.cloud.automl.v1beta1.BoundingPoly bounding_box = 1; * @return \Google\Cloud\AutoMl\V1beta1\BoundingPoly @@ -64,8 +59,7 @@ public function getBoundingBox() } /** - * Output only. - * The rectangle representing the object location. + * Output only. The rectangle representing the object location. * * Generated from protobuf field .google.cloud.automl.v1beta1.BoundingPoly bounding_box = 1; * @param \Google\Cloud\AutoMl\V1beta1\BoundingPoly $var @@ -80,8 +74,7 @@ public function setBoundingBox($var) } /** - * Output only. - * The confidence that this annotation is positive for the parent example, + * Output only. The confidence that this annotation is positive for the parent example, * value in [0, 1], higher means higher positivity confidence. * * Generated from protobuf field float score = 2; @@ -93,8 +86,7 @@ public function getScore() } /** - * Output only. - * The confidence that this annotation is positive for the parent example, + * Output only. The confidence that this annotation is positive for the parent example, * value in [0, 1], higher means higher positivity confidence. * * Generated from protobuf field float score = 2; diff --git a/AutoMl/src/V1beta1/ImageObjectDetectionModelMetadata.php b/AutoMl/src/V1beta1/ImageObjectDetectionModelMetadata.php index 30b5d921f5b5..5699388f4ba3 100644 --- a/AutoMl/src/V1beta1/ImageObjectDetectionModelMetadata.php +++ b/AutoMl/src/V1beta1/ImageObjectDetectionModelMetadata.php @@ -56,9 +56,16 @@ class ImageObjectDetectionModelMetadata extends \Google\Protobuf\Internal\Messag * `train_cost` will be equal or less than this value. If further model * training ceases to provide any improvements, it will stop without using * full budget and the stop_reason will be `MODEL_CONVERGED`. - * Note, node_hour = actual_hour * number_of_nodes_invovled. The train budget - * must be between 20,000 and 2,000,000 milli node hours, inclusive. The - * default value is 216, 000 which represents one day in wall time. + * Note, node_hour = actual_hour * number_of_nodes_invovled. + * For model type `cloud-high-accuracy-1`(default) and `cloud-low-latency-1`, + * the train budget must be between 20,000 and 2,000,000 milli node hours, + * inclusive. The default value is 216, 000 which represents one day in + * wall time. + * For model type `mobile-low-latency-1`, `mobile-versatile-1`, + * `mobile-high-accuracy-1`, `mobile-core-ml-low-latency-1`, + * `mobile-core-ml-versatile-1`, `mobile-core-ml-high-accuracy-1`, the train + * budget must be between 1,000 and 100,000 milli node hours, inclusive. + * The default value is 24, 000 which represents one day in wall time. * * Generated from protobuf field int64 train_budget_milli_node_hours = 6; */ @@ -103,9 +110,16 @@ class ImageObjectDetectionModelMetadata extends \Google\Protobuf\Internal\Messag * `train_cost` will be equal or less than this value. If further model * training ceases to provide any improvements, it will stop without using * full budget and the stop_reason will be `MODEL_CONVERGED`. - * Note, node_hour = actual_hour * number_of_nodes_invovled. The train budget - * must be between 20,000 and 2,000,000 milli node hours, inclusive. The - * default value is 216, 000 which represents one day in wall time. + * Note, node_hour = actual_hour * number_of_nodes_invovled. + * For model type `cloud-high-accuracy-1`(default) and `cloud-low-latency-1`, + * the train budget must be between 20,000 and 2,000,000 milli node hours, + * inclusive. The default value is 216, 000 which represents one day in + * wall time. + * For model type `mobile-low-latency-1`, `mobile-versatile-1`, + * `mobile-high-accuracy-1`, `mobile-core-ml-low-latency-1`, + * `mobile-core-ml-versatile-1`, `mobile-core-ml-high-accuracy-1`, the train + * budget must be between 1,000 and 100,000 milli node hours, inclusive. + * The default value is 24, 000 which represents one day in wall time. * @type int|string $train_cost_milli_node_hours * Output only. The actual train cost of creating this model, expressed in * milli node hours, i.e. 1,000 value in this field means 1 node hour. @@ -249,9 +263,16 @@ public function setStopReason($var) * `train_cost` will be equal or less than this value. If further model * training ceases to provide any improvements, it will stop without using * full budget and the stop_reason will be `MODEL_CONVERGED`. - * Note, node_hour = actual_hour * number_of_nodes_invovled. The train budget - * must be between 20,000 and 2,000,000 milli node hours, inclusive. The - * default value is 216, 000 which represents one day in wall time. + * Note, node_hour = actual_hour * number_of_nodes_invovled. + * For model type `cloud-high-accuracy-1`(default) and `cloud-low-latency-1`, + * the train budget must be between 20,000 and 2,000,000 milli node hours, + * inclusive. The default value is 216, 000 which represents one day in + * wall time. + * For model type `mobile-low-latency-1`, `mobile-versatile-1`, + * `mobile-high-accuracy-1`, `mobile-core-ml-low-latency-1`, + * `mobile-core-ml-versatile-1`, `mobile-core-ml-high-accuracy-1`, the train + * budget must be between 1,000 and 100,000 milli node hours, inclusive. + * The default value is 24, 000 which represents one day in wall time. * * Generated from protobuf field int64 train_budget_milli_node_hours = 6; * @return int|string @@ -267,9 +288,16 @@ public function getTrainBudgetMilliNodeHours() * `train_cost` will be equal or less than this value. If further model * training ceases to provide any improvements, it will stop without using * full budget and the stop_reason will be `MODEL_CONVERGED`. - * Note, node_hour = actual_hour * number_of_nodes_invovled. The train budget - * must be between 20,000 and 2,000,000 milli node hours, inclusive. The - * default value is 216, 000 which represents one day in wall time. + * Note, node_hour = actual_hour * number_of_nodes_invovled. + * For model type `cloud-high-accuracy-1`(default) and `cloud-low-latency-1`, + * the train budget must be between 20,000 and 2,000,000 milli node hours, + * inclusive. The default value is 216, 000 which represents one day in + * wall time. + * For model type `mobile-low-latency-1`, `mobile-versatile-1`, + * `mobile-high-accuracy-1`, `mobile-core-ml-low-latency-1`, + * `mobile-core-ml-versatile-1`, `mobile-core-ml-high-accuracy-1`, the train + * budget must be between 1,000 and 100,000 milli node hours, inclusive. + * The default value is 24, 000 which represents one day in wall time. * * Generated from protobuf field int64 train_budget_milli_node_hours = 6; * @param int|string $var diff --git a/AutoMl/src/V1beta1/InputConfig.php b/AutoMl/src/V1beta1/InputConfig.php index e599ab18a89b..6d9c70b28e32 100644 --- a/AutoMl/src/V1beta1/InputConfig.php +++ b/AutoMl/src/V1beta1/InputConfig.php @@ -15,10 +15,10 @@ * [gcs_source][google.cloud.automl.v1beta1.InputConfig.gcs_source] * is expected, unless specified otherwise. Additionally any input .CSV file * by itself must be 100MB or smaller, unless specified otherwise. - * If an "example" file (i.e. image, video etc.) with identical content + * If an "example" file (that is, image, video etc.) with identical content * (even if it had different GCS_FILE_PATH) is mentioned multiple times, then * its label, bounding boxes etc. are appended. The same file should be always - * provided with the same ML_USE and GCS_FILE_PATH, if it is not then + * provided with the same ML_USE and GCS_FILE_PATH, if it is not, then * these values are nondeterministically selected from the given ones. * The formats are represented in EBNF with commas being literal and with * non-terminal symbols defined near the end of this comment. The formats are: @@ -45,12 +45,16 @@ * BOUNDING_BOX-es per image are allowed (one BOUNDING_BOX is defined * per line). If an image has not yet been labeled, then it should be * mentioned just once with no LABEL and the ",,,,,,," in place of the + * BOUNDING_BOX. For images which are known to not contain any + * bounding boxes, they should be labelled explictly as + * "NEGATIVE_IMAGE", followed by ",,,,,,," in place of the * BOUNDING_BOX. - * Four sample rows: + * Sample rows: * TRAIN,gs://folder/image1.png,car,0.1,0.1,,,0.3,0.3,, * TRAIN,gs://folder/image1.png,bike,.7,.6,,,.8,.9,, * UNASSIGNED,gs://folder/im2.png,car,0.1,0.1,0.2,0.1,0.2,0.3,0.1,0.3 * TEST,gs://folder/im3.png,,,,,,,,, + * TRAIN,gs://folder/im4.png,NEGATIVE_IMAGE,,,,,,,,, * * For Video Classification: * CSV file(s) with each line in format: * ML_USE,GCS_FILE_PATH @@ -113,21 +117,21 @@ * * For Text Extraction: * CSV file(s) with each line in format: * ML_USE,GCS_FILE_PATH - * GCS_FILE_PATH leads to a .JSONL (i.e. JSON Lines) file which either - * imports text in-line or as documents. + * GCS_FILE_PATH leads to a .JSONL (that is, JSON Lines) file which + * either imports text in-line or as documents. * The in-line .JSONL file contains, per line, a proto that wraps a - * TextSnippet proto (in json representation) followed by one or - * more AnnotationPayload protos (called annotations), which have - * display_name and text_extraction detail populated. - * The given text is expected to be annotated exhaustively, e.g. if - * you look for animals and text contains "dolphin" that is not - * labeled, then "dolphin" will be assumed to not be an animal. Any - * given text snippet content must have 30,000 characters or less, - * and also be UTF-8 NFC encoded (ASCII already is). The document .JSONL file contains, per line, a proto that wraps a - * Document proto with input_config set. Only PDF documents are - * supported now, and each document may be up to 2MB large. - * Currently annotations on documents cannot be specified at import. - * Any given .JSONL file must be 100MB or smaller. + * TextSnippet proto (in json representation) followed by one or more + * AnnotationPayload protos (called annotations), which have + * display_name and text_extraction detail populated. The given text + * is expected to be annotated exhaustively, for example, if you look + * for animals and text contains "dolphin" that is not labeled, then + * "dolphin" is assumed to not be an animal. Any given text snippet + * content must have 30,000 characters or less, and also be UTF-8 NFC + * encoded (ASCII already is). The document .JSONL file contains, per line, a proto that wraps a + * Document proto with input_config set. Only PDF documents are + * supported now, and each document may be up to 2MB large. Currently + * annotations on documents cannot be specified at import. Any given + * .JSONL file must be 100MB or smaller. * Three sample CSV rows: * TRAIN,gs://folder/file1.jsonl * VALIDATE,gs://folder/file2.jsonl @@ -196,41 +200,41 @@ * TEXT_SNIPPET and GCS_FILE_PATH are distinguished by a pattern. If * the column content is a valid gcs file path, i.e. prefixed by * "gs://", it will be treated as a GCS_FILE_PATH, else if the content - * is enclosed within double quotes (""), it will - * be treated as a TEXT_SNIPPET. In the GCS_FILE_PATH case, the path - * must lead to a .txt file with UTF-8 encoding, e.g. - * "gs://folder/content.txt", and the content in it will be extracted + * is enclosed within double quotes (""), it is + * treated as a TEXT_SNIPPET. In the GCS_FILE_PATH case, the path + * must lead to a .txt file with UTF-8 encoding, for example, + * "gs://folder/content.txt", and the content in it is extracted * as a text snippet. In TEXT_SNIPPET case, the column content - * excluding quotes will be treated as to be imported text snippet. In + * excluding quotes is treated as to be imported text snippet. In * both cases, the text snippet/file size must be within 128kB. * Maximum 100 unique labels are allowed per CSV row. - * Four sample rows: - * TRAIN,"They have bad food and very rude",RudeService,BadFood - * TRAIN,gs://folder/content.txt,SlowService - * TEST,"Typically always bad service there.",RudeService - * VALIDATE,"Stomach ache to go.",BadFood + * Sample rows: + * TRAIN,"They have bad food and very rude",RudeService,BadFood + * TRAIN,gs://folder/content.txt,SlowService + * TEST,"Typically always bad service there.",RudeService + * VALIDATE,"Stomach ache to go.",BadFood * * For Text Sentiment: * CSV file(s) with each line in format: * ML_USE,(TEXT_SNIPPET | GCS_FILE_PATH),SENTIMENT * TEXT_SNIPPET and GCS_FILE_PATH are distinguished by a pattern. If - * the column content is a valid gcs file path, i.e. prefixed by - * "gs://", it will be treated as a GCS_FILE_PATH, otherwise it will - * be treated as a TEXT_SNIPPET. In the GCS_FILE_PATH case, the path - * must lead to a .txt file with UTF-8 encoding, e.g. - * "gs://folder/content.txt", and the content in it will be extracted + * the column content is a valid gcs file path, that is, prefixed by + * "gs://", it is treated as a GCS_FILE_PATH, otherwise it is treated + * as a TEXT_SNIPPET. In the GCS_FILE_PATH case, the path + * must lead to a .txt file with UTF-8 encoding, for example, + * "gs://folder/content.txt", and the content in it is extracted * as a text snippet. In TEXT_SNIPPET case, the column content itself - * will be treated as to be imported text snippet. In both cases, the + * is treated as to be imported text snippet. In both cases, the * text snippet must be up to 500 characters long. - * Four sample rows: - * TRAIN,"@freewrytin God is way too good for Claritin",2 - * TRAIN,"I need Claritin so bad",3 - * TEST,"Thank god for Claritin.",4 - * VALIDATE,gs://folder/content.txt,2 + * Sample rows: + * TRAIN,"@freewrytin this is way too good for your product",2 + * TRAIN,"I need this product so bad",3 + * TEST,"Thank you for this product.",4 + * VALIDATE,gs://folder/content.txt,2 * * For Tables: * Either * [gcs_source][google.cloud.automl.v1beta1.InputConfig.gcs_source] or * [bigquery_source][google.cloud.automl.v1beta1.InputConfig.bigquery_source] - * can be used. All inputs will be concatenated into a single + * can be used. All inputs is concatenated into a single * [primary_table][google.cloud.automl.v1beta1.TablesDatasetMetadata.primary_table_name] * For gcs_source: * CSV file(s), where the first row of the first file is the header, @@ -307,7 +311,7 @@ * If any of the provided CSV files can't be parsed or if more than certain * percent of CSV rows cannot be processed then the operation fails and * nothing is imported. Regardless of overall success or failure the per-row - * failures, up to a certain count cap, will be listed in + * failures, up to a certain count cap, is listed in * Operation.metadata.partial_failures. * * Generated from protobuf message google.cloud.automl.v1beta1.InputConfig diff --git a/AutoMl/src/V1beta1/Model.php b/AutoMl/src/V1beta1/Model.php index be57f58abbff..e5406adfa6a7 100644 --- a/AutoMl/src/V1beta1/Model.php +++ b/AutoMl/src/V1beta1/Model.php @@ -16,8 +16,7 @@ class Model extends \Google\Protobuf\Internal\Message { /** - * Output only. - * Resource name of the model. + * Output only. Resource name of the model. * Format: `projects/{project_id}/locations/{location_id}/models/{model_id}` * * Generated from protobuf field string name = 1; @@ -33,23 +32,20 @@ class Model extends \Google\Protobuf\Internal\Message */ private $display_name = ''; /** - * Required. - * The resource ID of the dataset used to create the model. The dataset must + * Required. The resource ID of the dataset used to create the model. The dataset must * come from the same ancestor project and location. * * Generated from protobuf field string dataset_id = 3; */ private $dataset_id = ''; /** - * Output only. - * Timestamp when the model training finished and can be used for prediction. + * Output only. Timestamp when the model training finished and can be used for prediction. * * Generated from protobuf field .google.protobuf.Timestamp create_time = 7; */ private $create_time = null; /** - * Output only. - * Timestamp when this model was last updated. + * Output only. Timestamp when this model was last updated. * * Generated from protobuf field .google.protobuf.Timestamp update_time = 11; */ @@ -88,8 +84,7 @@ class Model extends \Google\Protobuf\Internal\Message * @type \Google\Cloud\AutoMl\V1beta1\TextSentimentModelMetadata $text_sentiment_model_metadata * Metadata for text sentiment models. * @type string $name - * Output only. - * Resource name of the model. + * Output only. Resource name of the model. * Format: `projects/{project_id}/locations/{location_id}/models/{model_id}` * @type string $display_name * Required. The name of the model to show in the interface. The name can be @@ -97,15 +92,12 @@ class Model extends \Google\Protobuf\Internal\Message * and a-z, underscores * (_), and ASCII digits 0-9. It must start with a letter. * @type string $dataset_id - * Required. - * The resource ID of the dataset used to create the model. The dataset must + * Required. The resource ID of the dataset used to create the model. The dataset must * come from the same ancestor project and location. * @type \Google\Protobuf\Timestamp $create_time - * Output only. - * Timestamp when the model training finished and can be used for prediction. + * Output only. Timestamp when the model training finished and can be used for prediction. * @type \Google\Protobuf\Timestamp $update_time - * Output only. - * Timestamp when this model was last updated. + * Output only. Timestamp when this model was last updated. * @type int $deployment_state * Output only. Deployment state of the model. A model can only serve * prediction requests after it gets deployed. @@ -351,8 +343,7 @@ public function setTextSentimentModelMetadata($var) } /** - * Output only. - * Resource name of the model. + * Output only. Resource name of the model. * Format: `projects/{project_id}/locations/{location_id}/models/{model_id}` * * Generated from protobuf field string name = 1; @@ -364,8 +355,7 @@ public function getName() } /** - * Output only. - * Resource name of the model. + * Output only. Resource name of the model. * Format: `projects/{project_id}/locations/{location_id}/models/{model_id}` * * Generated from protobuf field string name = 1; @@ -413,8 +403,7 @@ public function setDisplayName($var) } /** - * Required. - * The resource ID of the dataset used to create the model. The dataset must + * Required. The resource ID of the dataset used to create the model. The dataset must * come from the same ancestor project and location. * * Generated from protobuf field string dataset_id = 3; @@ -426,8 +415,7 @@ public function getDatasetId() } /** - * Required. - * The resource ID of the dataset used to create the model. The dataset must + * Required. The resource ID of the dataset used to create the model. The dataset must * come from the same ancestor project and location. * * Generated from protobuf field string dataset_id = 3; @@ -443,8 +431,7 @@ public function setDatasetId($var) } /** - * Output only. - * Timestamp when the model training finished and can be used for prediction. + * Output only. Timestamp when the model training finished and can be used for prediction. * * Generated from protobuf field .google.protobuf.Timestamp create_time = 7; * @return \Google\Protobuf\Timestamp @@ -455,8 +442,7 @@ public function getCreateTime() } /** - * Output only. - * Timestamp when the model training finished and can be used for prediction. + * Output only. Timestamp when the model training finished and can be used for prediction. * * Generated from protobuf field .google.protobuf.Timestamp create_time = 7; * @param \Google\Protobuf\Timestamp $var @@ -471,8 +457,7 @@ public function setCreateTime($var) } /** - * Output only. - * Timestamp when this model was last updated. + * Output only. Timestamp when this model was last updated. * * Generated from protobuf field .google.protobuf.Timestamp update_time = 11; * @return \Google\Protobuf\Timestamp @@ -483,8 +468,7 @@ public function getUpdateTime() } /** - * Output only. - * Timestamp when this model was last updated. + * Output only. Timestamp when this model was last updated. * * Generated from protobuf field .google.protobuf.Timestamp update_time = 11; * @param \Google\Protobuf\Timestamp $var diff --git a/AutoMl/src/V1beta1/ModelEvaluation.php b/AutoMl/src/V1beta1/ModelEvaluation.php index dd179570c826..b99ff6199c7e 100644 --- a/AutoMl/src/V1beta1/ModelEvaluation.php +++ b/AutoMl/src/V1beta1/ModelEvaluation.php @@ -16,8 +16,7 @@ class ModelEvaluation extends \Google\Protobuf\Internal\Message { /** - * Output only. - * Resource name of the model evaluation. + * Output only. Resource name of the model evaluation. * Format: * `projects/{project_id}/locations/{location_id}/models/{model_id}/modelEvaluations/{model_evaluation_id}` * @@ -25,8 +24,7 @@ class ModelEvaluation extends \Google\Protobuf\Internal\Message */ private $name = ''; /** - * Output only. - * The ID of the annotation spec that the model evaluation applies to. The + * Output only. The ID of the annotation spec that the model evaluation applies to. The * The ID is empty for the overall model evaluation. * For Tables annotation specs in the dataset do not exist and this ID is * always not set, but for CLASSIFICATION @@ -40,7 +38,7 @@ class ModelEvaluation extends \Google\Protobuf\Internal\Message private $annotation_spec_id = ''; /** * Output only. The value of - * [display_name][google.cloud.automl.v1beta1.AnnotationSpec.dispay_name] at + * [display_name][google.cloud.automl.v1beta1.AnnotationSpec.display_name] at * the moment when the model was trained. Because this field returns a value * at model training time, for different models trained from the same dataset, * the values may differ, since display names could had been changed between @@ -55,15 +53,13 @@ class ModelEvaluation extends \Google\Protobuf\Internal\Message */ private $display_name = ''; /** - * Output only. - * Timestamp when this model evaluation was created. + * Output only. Timestamp when this model evaluation was created. * * Generated from protobuf field .google.protobuf.Timestamp create_time = 5; */ private $create_time = null; /** - * Output only. - * The number of examples used for model evaluation, i.e. for + * Output only. The number of examples used for model evaluation, i.e. for * which ground truth from time of model creation is compared against the * predicted annotations created by the model. * For overall ModelEvaluation (i.e. with annotation_spec_id not set) this is @@ -103,13 +99,11 @@ class ModelEvaluation extends \Google\Protobuf\Internal\Message * @type \Google\Cloud\AutoMl\V1beta1\TextExtractionEvaluationMetrics $text_extraction_evaluation_metrics * Evaluation metrics for text extraction models. * @type string $name - * Output only. - * Resource name of the model evaluation. + * Output only. Resource name of the model evaluation. * Format: * `projects/{project_id}/locations/{location_id}/models/{model_id}/modelEvaluations/{model_evaluation_id}` * @type string $annotation_spec_id - * Output only. - * The ID of the annotation spec that the model evaluation applies to. The + * Output only. The ID of the annotation spec that the model evaluation applies to. The * The ID is empty for the overall model evaluation. * For Tables annotation specs in the dataset do not exist and this ID is * always not set, but for CLASSIFICATION @@ -119,7 +113,7 @@ class ModelEvaluation extends \Google\Protobuf\Internal\Message * field is used. * @type string $display_name * Output only. The value of - * [display_name][google.cloud.automl.v1beta1.AnnotationSpec.dispay_name] at + * [display_name][google.cloud.automl.v1beta1.AnnotationSpec.display_name] at * the moment when the model was trained. Because this field returns a value * at model training time, for different models trained from the same dataset, * the values may differ, since display names could had been changed between @@ -130,11 +124,9 @@ class ModelEvaluation extends \Google\Protobuf\Internal\Message * are populated here. * The display_name is empty for the overall model evaluation. * @type \Google\Protobuf\Timestamp $create_time - * Output only. - * Timestamp when this model evaluation was created. + * Output only. Timestamp when this model evaluation was created. * @type int $evaluated_example_count - * Output only. - * The number of examples used for model evaluation, i.e. for + * Output only. The number of examples used for model evaluation, i.e. for * which ground truth from time of model creation is compared against the * predicted annotations created by the model. * For overall ModelEvaluation (i.e. with annotation_spec_id not set) this is @@ -342,8 +334,7 @@ public function setTextExtractionEvaluationMetrics($var) } /** - * Output only. - * Resource name of the model evaluation. + * Output only. Resource name of the model evaluation. * Format: * `projects/{project_id}/locations/{location_id}/models/{model_id}/modelEvaluations/{model_evaluation_id}` * @@ -356,8 +347,7 @@ public function getName() } /** - * Output only. - * Resource name of the model evaluation. + * Output only. Resource name of the model evaluation. * Format: * `projects/{project_id}/locations/{location_id}/models/{model_id}/modelEvaluations/{model_evaluation_id}` * @@ -374,8 +364,7 @@ public function setName($var) } /** - * Output only. - * The ID of the annotation spec that the model evaluation applies to. The + * Output only. The ID of the annotation spec that the model evaluation applies to. The * The ID is empty for the overall model evaluation. * For Tables annotation specs in the dataset do not exist and this ID is * always not set, but for CLASSIFICATION @@ -393,8 +382,7 @@ public function getAnnotationSpecId() } /** - * Output only. - * The ID of the annotation spec that the model evaluation applies to. The + * Output only. The ID of the annotation spec that the model evaluation applies to. The * The ID is empty for the overall model evaluation. * For Tables annotation specs in the dataset do not exist and this ID is * always not set, but for CLASSIFICATION @@ -417,7 +405,7 @@ public function setAnnotationSpecId($var) /** * Output only. The value of - * [display_name][google.cloud.automl.v1beta1.AnnotationSpec.dispay_name] at + * [display_name][google.cloud.automl.v1beta1.AnnotationSpec.display_name] at * the moment when the model was trained. Because this field returns a value * at model training time, for different models trained from the same dataset, * the values may differ, since display names could had been changed between @@ -438,7 +426,7 @@ public function getDisplayName() /** * Output only. The value of - * [display_name][google.cloud.automl.v1beta1.AnnotationSpec.dispay_name] at + * [display_name][google.cloud.automl.v1beta1.AnnotationSpec.display_name] at * the moment when the model was trained. Because this field returns a value * at model training time, for different models trained from the same dataset, * the values may differ, since display names could had been changed between @@ -462,8 +450,7 @@ public function setDisplayName($var) } /** - * Output only. - * Timestamp when this model evaluation was created. + * Output only. Timestamp when this model evaluation was created. * * Generated from protobuf field .google.protobuf.Timestamp create_time = 5; * @return \Google\Protobuf\Timestamp @@ -474,8 +461,7 @@ public function getCreateTime() } /** - * Output only. - * Timestamp when this model evaluation was created. + * Output only. Timestamp when this model evaluation was created. * * Generated from protobuf field .google.protobuf.Timestamp create_time = 5; * @param \Google\Protobuf\Timestamp $var @@ -490,8 +476,7 @@ public function setCreateTime($var) } /** - * Output only. - * The number of examples used for model evaluation, i.e. for + * Output only. The number of examples used for model evaluation, i.e. for * which ground truth from time of model creation is compared against the * predicted annotations created by the model. * For overall ModelEvaluation (i.e. with annotation_spec_id not set) this is @@ -509,8 +494,7 @@ public function getEvaluatedExampleCount() } /** - * Output only. - * The number of examples used for model evaluation, i.e. for + * Output only. The number of examples used for model evaluation, i.e. for * which ground truth from time of model creation is compared against the * predicted annotations created by the model. * For overall ModelEvaluation (i.e. with annotation_spec_id not set) this is diff --git a/AutoMl/src/V1beta1/ModelExportOutputConfig.php b/AutoMl/src/V1beta1/ModelExportOutputConfig.php index b534b1195665..128eb56ec28b 100644 --- a/AutoMl/src/V1beta1/ModelExportOutputConfig.php +++ b/AutoMl/src/V1beta1/ModelExportOutputConfig.php @@ -34,7 +34,9 @@ class ModelExportOutputConfig extends \Google\Protobuf\Internal\Message * * docker - Used for Docker containers. Use the params field to customize * the container. The container is verified to work correctly on * ubuntu 16.04 operating system. See more at - * [containers quickstart](https://cloud.google.com/vision/automl/docs/containers-gcs-quickstart) + * [containers + * quickstart](https: + * //cloud.google.com/vision/automl/docs/containers-gcs-quickstart) * * core_ml - Used for iOS mobile devices. * * Generated from protobuf field string model_format = 4; @@ -92,7 +94,9 @@ class ModelExportOutputConfig extends \Google\Protobuf\Internal\Message * * docker - Used for Docker containers. Use the params field to customize * the container. The container is verified to work correctly on * ubuntu 16.04 operating system. See more at - * [containers quickstart](https://cloud.google.com/vision/automl/docs/containers-gcs-quickstart) + * [containers + * quickstart](https: + * //cloud.google.com/vision/automl/docs/containers-gcs-quickstart) * * core_ml - Used for iOS mobile devices. * @type array|\Google\Protobuf\Internal\MapField $params * Additional model-type and format specific parameters describing the @@ -199,7 +203,9 @@ public function setGcrDestination($var) * * docker - Used for Docker containers. Use the params field to customize * the container. The container is verified to work correctly on * ubuntu 16.04 operating system. See more at - * [containers quickstart](https://cloud.google.com/vision/automl/docs/containers-gcs-quickstart) + * [containers + * quickstart](https: + * //cloud.google.com/vision/automl/docs/containers-gcs-quickstart) * * core_ml - Used for iOS mobile devices. * * Generated from protobuf field string model_format = 4; @@ -229,7 +235,9 @@ public function getModelFormat() * * docker - Used for Docker containers. Use the params field to customize * the container. The container is verified to work correctly on * ubuntu 16.04 operating system. See more at - * [containers quickstart](https://cloud.google.com/vision/automl/docs/containers-gcs-quickstart) + * [containers + * quickstart](https: + * //cloud.google.com/vision/automl/docs/containers-gcs-quickstart) * * core_ml - Used for iOS mobile devices. * * Generated from protobuf field string model_format = 4; diff --git a/AutoMl/src/V1beta1/PredictRequest.php b/AutoMl/src/V1beta1/PredictRequest.php index be7cc51ca7cb..8530308feda7 100644 --- a/AutoMl/src/V1beta1/PredictRequest.php +++ b/AutoMl/src/V1beta1/PredictRequest.php @@ -22,8 +22,7 @@ class PredictRequest extends \Google\Protobuf\Internal\Message */ private $name = ''; /** - * Required. - * Payload to perform a prediction on. The payload must match the + * Required. Payload to perform a prediction on. The payload must match the * problem type that the model was trained to solve. * * Generated from protobuf field .google.cloud.automl.v1beta1.ExamplePayload payload = 2; @@ -36,6 +35,13 @@ class PredictRequest extends \Google\Protobuf\Internal\Message * `score_threshold` - (float) A value from 0.0 to 1.0. When the model * makes predictions for an image, it will only produce results that have * at least this confidence score. The default is 0.5. + * * For Image Object Detection: + * `score_threshold` - (float) When Model detects objects on the image, + * it will only produce bounding boxes which have at least this + * confidence score. Value in 0 to 1 range, default is 0.5. + * `max_bounding_box_count` - (int64) No more than this number of bounding + * boxes will be returned in the response. Default is 100, the + * requested value may be limited by server. * * For Tables: * `feature_importance` - (boolean) Whether * [feature_importance][[google.cloud.automl.v1beta1.TablesModelColumnInfo.feature_importance] @@ -56,8 +62,7 @@ class PredictRequest extends \Google\Protobuf\Internal\Message * @type string $name * Name of the model requested to serve the prediction. * @type \Google\Cloud\AutoMl\V1beta1\ExamplePayload $payload - * Required. - * Payload to perform a prediction on. The payload must match the + * Required. Payload to perform a prediction on. The payload must match the * problem type that the model was trained to solve. * @type array|\Google\Protobuf\Internal\MapField $params * Additional domain-specific parameters, any string must be up to 25000 @@ -66,6 +71,13 @@ class PredictRequest extends \Google\Protobuf\Internal\Message * `score_threshold` - (float) A value from 0.0 to 1.0. When the model * makes predictions for an image, it will only produce results that have * at least this confidence score. The default is 0.5. + * * For Image Object Detection: + * `score_threshold` - (float) When Model detects objects on the image, + * it will only produce bounding boxes which have at least this + * confidence score. Value in 0 to 1 range, default is 0.5. + * `max_bounding_box_count` - (int64) No more than this number of bounding + * boxes will be returned in the response. Default is 100, the + * requested value may be limited by server. * * For Tables: * `feature_importance` - (boolean) Whether * [feature_importance][[google.cloud.automl.v1beta1.TablesModelColumnInfo.feature_importance] @@ -106,8 +118,7 @@ public function setName($var) } /** - * Required. - * Payload to perform a prediction on. The payload must match the + * Required. Payload to perform a prediction on. The payload must match the * problem type that the model was trained to solve. * * Generated from protobuf field .google.cloud.automl.v1beta1.ExamplePayload payload = 2; @@ -119,8 +130,7 @@ public function getPayload() } /** - * Required. - * Payload to perform a prediction on. The payload must match the + * Required. Payload to perform a prediction on. The payload must match the * problem type that the model was trained to solve. * * Generated from protobuf field .google.cloud.automl.v1beta1.ExamplePayload payload = 2; @@ -142,6 +152,13 @@ public function setPayload($var) * `score_threshold` - (float) A value from 0.0 to 1.0. When the model * makes predictions for an image, it will only produce results that have * at least this confidence score. The default is 0.5. + * * For Image Object Detection: + * `score_threshold` - (float) When Model detects objects on the image, + * it will only produce bounding boxes which have at least this + * confidence score. Value in 0 to 1 range, default is 0.5. + * `max_bounding_box_count` - (int64) No more than this number of bounding + * boxes will be returned in the response. Default is 100, the + * requested value may be limited by server. * * For Tables: * `feature_importance` - (boolean) Whether * [feature_importance][[google.cloud.automl.v1beta1.TablesModelColumnInfo.feature_importance] @@ -164,6 +181,13 @@ public function getParams() * `score_threshold` - (float) A value from 0.0 to 1.0. When the model * makes predictions for an image, it will only produce results that have * at least this confidence score. The default is 0.5. + * * For Image Object Detection: + * `score_threshold` - (float) When Model detects objects on the image, + * it will only produce bounding boxes which have at least this + * confidence score. Value in 0 to 1 range, default is 0.5. + * `max_bounding_box_count` - (int64) No more than this number of bounding + * boxes will be returned in the response. Default is 100, the + * requested value may be limited by server. * * For Tables: * `feature_importance` - (boolean) Whether * [feature_importance][[google.cloud.automl.v1beta1.TablesModelColumnInfo.feature_importance] diff --git a/AutoMl/src/V1beta1/PredictionServiceGrpcClient.php b/AutoMl/src/V1beta1/PredictionServiceGrpcClient.php index d2a7149132bd..7f58c6db7ac0 100644 --- a/AutoMl/src/V1beta1/PredictionServiceGrpcClient.php +++ b/AutoMl/src/V1beta1/PredictionServiceGrpcClient.php @@ -54,6 +54,8 @@ public function __construct($hostname, $opts, $channel = null) { * up to 5MB. Not available for FORECASTING * * [prediction_type][google.cloud.automl.v1beta1.TablesModelMetadata.prediction_type]. + * * Text Sentiment - TextSnippet, content up 500 characters, UTF-8 + * encoded. * @param \Google\Cloud\AutoMl\V1beta1\PredictRequest $argument input argument * @param array $metadata metadata * @param array $options call options @@ -74,9 +76,10 @@ public function Predict(\Google\Cloud\AutoMl\V1beta1\PredictRequest $argument, * method. Once the operation is done, [BatchPredictResult][google.cloud.automl.v1beta1.BatchPredictResult] is returned in * the [response][google.longrunning.Operation.response] field. * Available for following ML problems: + * * Image Classification + * * Image Object Detection * * Video Classification - * * Video Object Tracking - * * Text Extraction + * * Video Object Tracking * Text Extraction * * Tables * @param \Google\Cloud\AutoMl\V1beta1\BatchPredictRequest $argument input argument * @param array $metadata metadata diff --git a/AutoMl/src/V1beta1/Row.php b/AutoMl/src/V1beta1/Row.php index 7e634f8805c3..4d515ab832d2 100644 --- a/AutoMl/src/V1beta1/Row.php +++ b/AutoMl/src/V1beta1/Row.php @@ -16,9 +16,9 @@ class Row extends \Google\Protobuf\Internal\Message { /** - * Input Only. * The resource IDs of the column specs describing the columns of the row. - * If set must contain, but possibly in a different order, all input feature + * If set must contain, but possibly in a different order, all input + * feature * [column_spec_ids][google.cloud.automl.v1beta1.TablesModelMetadata.input_feature_column_specs] * of the Model this row is being passed to. * Note: The below `values` field must match order of this field, if this @@ -28,9 +28,9 @@ class Row extends \Google\Protobuf\Internal\Message */ private $column_spec_ids; /** - * Input Only. - * The values of the row cells, given in the same order as the - * column_spec_ids, or, if not set, then in the same order as input feature + * Required. The values of the row cells, given in the same order as the + * column_spec_ids, or, if not set, then in the same order as input + * feature * [column_specs][google.cloud.automl.v1beta1.TablesModelMetadata.input_feature_column_specs] * of the Model this row is being passed to. * @@ -45,17 +45,17 @@ class Row extends \Google\Protobuf\Internal\Message * Optional. Data for populating the Message object. * * @type string[]|\Google\Protobuf\Internal\RepeatedField $column_spec_ids - * Input Only. * The resource IDs of the column specs describing the columns of the row. - * If set must contain, but possibly in a different order, all input feature + * If set must contain, but possibly in a different order, all input + * feature * [column_spec_ids][google.cloud.automl.v1beta1.TablesModelMetadata.input_feature_column_specs] * of the Model this row is being passed to. * Note: The below `values` field must match order of this field, if this * field is set. * @type \Google\Protobuf\Value[]|\Google\Protobuf\Internal\RepeatedField $values - * Input Only. - * The values of the row cells, given in the same order as the - * column_spec_ids, or, if not set, then in the same order as input feature + * Required. The values of the row cells, given in the same order as the + * column_spec_ids, or, if not set, then in the same order as input + * feature * [column_specs][google.cloud.automl.v1beta1.TablesModelMetadata.input_feature_column_specs] * of the Model this row is being passed to. * } @@ -66,9 +66,9 @@ public function __construct($data = NULL) { } /** - * Input Only. * The resource IDs of the column specs describing the columns of the row. - * If set must contain, but possibly in a different order, all input feature + * If set must contain, but possibly in a different order, all input + * feature * [column_spec_ids][google.cloud.automl.v1beta1.TablesModelMetadata.input_feature_column_specs] * of the Model this row is being passed to. * Note: The below `values` field must match order of this field, if this @@ -83,9 +83,9 @@ public function getColumnSpecIds() } /** - * Input Only. * The resource IDs of the column specs describing the columns of the row. - * If set must contain, but possibly in a different order, all input feature + * If set must contain, but possibly in a different order, all input + * feature * [column_spec_ids][google.cloud.automl.v1beta1.TablesModelMetadata.input_feature_column_specs] * of the Model this row is being passed to. * Note: The below `values` field must match order of this field, if this @@ -104,9 +104,9 @@ public function setColumnSpecIds($var) } /** - * Input Only. - * The values of the row cells, given in the same order as the - * column_spec_ids, or, if not set, then in the same order as input feature + * Required. The values of the row cells, given in the same order as the + * column_spec_ids, or, if not set, then in the same order as input + * feature * [column_specs][google.cloud.automl.v1beta1.TablesModelMetadata.input_feature_column_specs] * of the Model this row is being passed to. * @@ -119,9 +119,9 @@ public function getValues() } /** - * Input Only. - * The values of the row cells, given in the same order as the - * column_spec_ids, or, if not set, then in the same order as input feature + * Required. The values of the row cells, given in the same order as the + * column_spec_ids, or, if not set, then in the same order as input + * feature * [column_specs][google.cloud.automl.v1beta1.TablesModelMetadata.input_feature_column_specs] * of the Model this row is being passed to. * diff --git a/AutoMl/src/V1beta1/TableSpec.php b/AutoMl/src/V1beta1/TableSpec.php index e23a9aa82d0d..ee198751e645 100644 --- a/AutoMl/src/V1beta1/TableSpec.php +++ b/AutoMl/src/V1beta1/TableSpec.php @@ -50,6 +50,13 @@ class TableSpec extends \Google\Protobuf\Internal\Message * Generated from protobuf field int64 row_count = 3; */ private $row_count = 0; + /** + * Output only. The number of valid rows (i.e. without values that don't match + * DataType-s of their columns). + * + * Generated from protobuf field int64 valid_row_count = 4; + */ + private $valid_row_count = 0; /** * Output only. The number of columns of the table. That is, the number of * child ColumnSpec-s. @@ -93,6 +100,9 @@ class TableSpec extends \Google\Protobuf\Internal\Message * affect any other users concurrently working with the dataset. * @type int|string $row_count * Output only. The number of rows (i.e. examples) in the table. + * @type int|string $valid_row_count + * Output only. The number of valid rows (i.e. without values that don't match + * DataType-s of their columns). * @type int|string $column_count * Output only. The number of columns of the table. That is, the number of * child ColumnSpec-s. @@ -205,6 +215,34 @@ public function setRowCount($var) return $this; } + /** + * Output only. The number of valid rows (i.e. without values that don't match + * DataType-s of their columns). + * + * Generated from protobuf field int64 valid_row_count = 4; + * @return int|string + */ + public function getValidRowCount() + { + return $this->valid_row_count; + } + + /** + * Output only. The number of valid rows (i.e. without values that don't match + * DataType-s of their columns). + * + * Generated from protobuf field int64 valid_row_count = 4; + * @param int|string $var + * @return $this + */ + public function setValidRowCount($var) + { + GPBUtil::checkInt64($var); + $this->valid_row_count = $var; + + return $this; + } + /** * Output only. The number of columns of the table. That is, the number of * child ColumnSpec-s. diff --git a/AutoMl/src/V1beta1/TablesAnnotation.php b/AutoMl/src/V1beta1/TablesAnnotation.php index 6190aef39f6c..48c49104f3e5 100644 --- a/AutoMl/src/V1beta1/TablesAnnotation.php +++ b/AutoMl/src/V1beta1/TablesAnnotation.php @@ -38,9 +38,9 @@ class TablesAnnotation extends \Google\Protobuf\Internal\Message * The predicted value of the row's * [target_column][google.cloud.automl.v1beta1.TablesModelMetadata.target_column_spec]. * The value depends on the column's DataType: - * CATEGORY - the predicted (with the above confidence `score`) CATEGORY - * value. - * FLOAT64 - the predicted (with above `prediction_interval`) FLOAT64 value. + * * CATEGORY - the predicted (with the above confidence `score`) CATEGORY + * value. + * * FLOAT64 - the predicted (with above `prediction_interval`) FLOAT64 value. * * Generated from protobuf field .google.protobuf.Value value = 2; */ @@ -80,9 +80,9 @@ class TablesAnnotation extends \Google\Protobuf\Internal\Message * The predicted value of the row's * [target_column][google.cloud.automl.v1beta1.TablesModelMetadata.target_column_spec]. * The value depends on the column's DataType: - * CATEGORY - the predicted (with the above confidence `score`) CATEGORY - * value. - * FLOAT64 - the predicted (with above `prediction_interval`) FLOAT64 value. + * * CATEGORY - the predicted (with the above confidence `score`) CATEGORY + * value. + * * FLOAT64 - the predicted (with above `prediction_interval`) FLOAT64 value. * @type \Google\Cloud\AutoMl\V1beta1\TablesModelColumnInfo[]|\Google\Protobuf\Internal\RepeatedField $tables_model_column_info * Output only. Auxiliary information for each of the model's * [input_feature_column_specs][google.cloud.automl.v1beta1.TablesModelMetadata.input_feature_column_specs] @@ -169,9 +169,9 @@ public function setPredictionInterval($var) * The predicted value of the row's * [target_column][google.cloud.automl.v1beta1.TablesModelMetadata.target_column_spec]. * The value depends on the column's DataType: - * CATEGORY - the predicted (with the above confidence `score`) CATEGORY - * value. - * FLOAT64 - the predicted (with above `prediction_interval`) FLOAT64 value. + * * CATEGORY - the predicted (with the above confidence `score`) CATEGORY + * value. + * * FLOAT64 - the predicted (with above `prediction_interval`) FLOAT64 value. * * Generated from protobuf field .google.protobuf.Value value = 2; * @return \Google\Protobuf\Value @@ -185,9 +185,9 @@ public function getValue() * The predicted value of the row's * [target_column][google.cloud.automl.v1beta1.TablesModelMetadata.target_column_spec]. * The value depends on the column's DataType: - * CATEGORY - the predicted (with the above confidence `score`) CATEGORY - * value. - * FLOAT64 - the predicted (with above `prediction_interval`) FLOAT64 value. + * * CATEGORY - the predicted (with the above confidence `score`) CATEGORY + * value. + * * FLOAT64 - the predicted (with above `prediction_interval`) FLOAT64 value. * * Generated from protobuf field .google.protobuf.Value value = 2; * @param \Google\Protobuf\Value $var diff --git a/AutoMl/src/V1beta1/TablesDatasetMetadata.php b/AutoMl/src/V1beta1/TablesDatasetMetadata.php index a111f803169c..e16c6ea849e0 100644 --- a/AutoMl/src/V1beta1/TablesDatasetMetadata.php +++ b/AutoMl/src/V1beta1/TablesDatasetMetadata.php @@ -28,7 +28,7 @@ class TablesDatasetMetadata extends \Google\Protobuf\Internal\Message * (otherwise model creation will error): * * CATEGORY * * FLOAT64 - * Furthermore, if the type is CATEGORY , then only up to + * If the type is CATEGORY , only up to * 100 unique values may exist in that column across all rows. * NOTE: Updates of this field will instantly affect any other users * concurrently working with the dataset. @@ -82,11 +82,12 @@ class TablesDatasetMetadata extends \Google\Protobuf\Internal\Message */ private $target_column_correlations; /** - * The most recent timestamp when target_column_correlations field and all - * descendant ColumnSpec.data_stats and ColumnSpec.top_correlated_columns - * fields were last (re-)generated. Any changes that happened to the dataset - * afterwards are not reflected in these fields values. The regeneration - * happens in the background on a best effort basis. + * Output only. The most recent timestamp when target_column_correlations + * field and all descendant ColumnSpec.data_stats and + * ColumnSpec.top_correlated_columns fields were last (re-)generated. Any + * changes that happened to the dataset afterwards are not reflected in these + * fields values. The regeneration happens in the background on a best effort + * basis. * * Generated from protobuf field .google.protobuf.Timestamp stats_update_time = 7; */ @@ -107,7 +108,7 @@ class TablesDatasetMetadata extends \Google\Protobuf\Internal\Message * (otherwise model creation will error): * * CATEGORY * * FLOAT64 - * Furthermore, if the type is CATEGORY , then only up to + * If the type is CATEGORY , only up to * 100 unique values may exist in that column across all rows. * NOTE: Updates of this field will instantly affect any other users * concurrently working with the dataset. @@ -145,11 +146,12 @@ class TablesDatasetMetadata extends \Google\Protobuf\Internal\Message * This field may be stale, see the stats_update_time field for * for the timestamp at which these stats were last updated. * @type \Google\Protobuf\Timestamp $stats_update_time - * The most recent timestamp when target_column_correlations field and all - * descendant ColumnSpec.data_stats and ColumnSpec.top_correlated_columns - * fields were last (re-)generated. Any changes that happened to the dataset - * afterwards are not reflected in these fields values. The regeneration - * happens in the background on a best effort basis. + * Output only. The most recent timestamp when target_column_correlations + * field and all descendant ColumnSpec.data_stats and + * ColumnSpec.top_correlated_columns fields were last (re-)generated. Any + * changes that happened to the dataset afterwards are not reflected in these + * fields values. The regeneration happens in the background on a best effort + * basis. * } */ public function __construct($data = NULL) { @@ -190,7 +192,7 @@ public function setPrimaryTableSpecId($var) * (otherwise model creation will error): * * CATEGORY * * FLOAT64 - * Furthermore, if the type is CATEGORY , then only up to + * If the type is CATEGORY , only up to * 100 unique values may exist in that column across all rows. * NOTE: Updates of this field will instantly affect any other users * concurrently working with the dataset. @@ -210,7 +212,7 @@ public function getTargetColumnSpecId() * (otherwise model creation will error): * * CATEGORY * * FLOAT64 - * Furthermore, if the type is CATEGORY , then only up to + * If the type is CATEGORY , only up to * 100 unique values may exist in that column across all rows. * NOTE: Updates of this field will instantly affect any other users * concurrently working with the dataset. @@ -360,11 +362,12 @@ public function setTargetColumnCorrelations($var) } /** - * The most recent timestamp when target_column_correlations field and all - * descendant ColumnSpec.data_stats and ColumnSpec.top_correlated_columns - * fields were last (re-)generated. Any changes that happened to the dataset - * afterwards are not reflected in these fields values. The regeneration - * happens in the background on a best effort basis. + * Output only. The most recent timestamp when target_column_correlations + * field and all descendant ColumnSpec.data_stats and + * ColumnSpec.top_correlated_columns fields were last (re-)generated. Any + * changes that happened to the dataset afterwards are not reflected in these + * fields values. The regeneration happens in the background on a best effort + * basis. * * Generated from protobuf field .google.protobuf.Timestamp stats_update_time = 7; * @return \Google\Protobuf\Timestamp @@ -375,11 +378,12 @@ public function getStatsUpdateTime() } /** - * The most recent timestamp when target_column_correlations field and all - * descendant ColumnSpec.data_stats and ColumnSpec.top_correlated_columns - * fields were last (re-)generated. Any changes that happened to the dataset - * afterwards are not reflected in these fields values. The regeneration - * happens in the background on a best effort basis. + * Output only. The most recent timestamp when target_column_correlations + * field and all descendant ColumnSpec.data_stats and + * ColumnSpec.top_correlated_columns fields were last (re-)generated. Any + * changes that happened to the dataset afterwards are not reflected in these + * fields values. The regeneration happens in the background on a best effort + * basis. * * Generated from protobuf field .google.protobuf.Timestamp stats_update_time = 7; * @param \Google\Protobuf\Timestamp $var diff --git a/AutoMl/src/V1beta1/TablesModelColumnInfo.php b/AutoMl/src/V1beta1/TablesModelColumnInfo.php index a76092f70aac..a7a51a3b1f33 100644 --- a/AutoMl/src/V1beta1/TablesModelColumnInfo.php +++ b/AutoMl/src/V1beta1/TablesModelColumnInfo.php @@ -31,8 +31,7 @@ class TablesModelColumnInfo extends \Google\Protobuf\Internal\Message */ private $column_display_name = ''; /** - * Output only. - * When given as part of a Model (always populated): + * Output only. When given as part of a Model (always populated): * Measurement of how much model predictions correctness on the TEST data * depend on values in this column. A value between 0 and 1, higher means * higher influence. These values are normalized - for all input feature @@ -65,8 +64,7 @@ class TablesModelColumnInfo extends \Google\Protobuf\Internal\Message * Output only. The display name of the column (same as the display_name of * its ColumnSpec). * @type float $feature_importance - * Output only. - * When given as part of a Model (always populated): + * Output only. When given as part of a Model (always populated): * Measurement of how much model predictions correctness on the TEST data * depend on values in this column. A value between 0 and 1, higher means * higher influence. These values are normalized - for all input feature @@ -145,8 +143,7 @@ public function setColumnDisplayName($var) } /** - * Output only. - * When given as part of a Model (always populated): + * Output only. When given as part of a Model (always populated): * Measurement of how much model predictions correctness on the TEST data * depend on values in this column. A value between 0 and 1, higher means * higher influence. These values are normalized - for all input feature @@ -171,8 +168,7 @@ public function getFeatureImportance() } /** - * Output only. - * When given as part of a Model (always populated): + * Output only. When given as part of a Model (always populated): * Measurement of how much model predictions correctness on the TEST data * depend on values in this column. A value between 0 and 1, higher means * higher influence. These values are normalized - for all input feature diff --git a/AutoMl/src/V1beta1/TablesModelMetadata.php b/AutoMl/src/V1beta1/TablesModelMetadata.php index d8590b945f7f..0a47c782ebfb 100644 --- a/AutoMl/src/V1beta1/TablesModelMetadata.php +++ b/AutoMl/src/V1beta1/TablesModelMetadata.php @@ -40,11 +40,11 @@ class TablesModelMetadata extends \Google\Protobuf\Internal\Message * [ml_use_column][google.cloud.automl.v1beta1.TablesDatasetMetadata.ml_use_column_spec_id] * must never be included here. * Only 3 fields are used: - * name - May be set on CreateModel, if set only the columns specified are - * used, otherwise all primary table's columns (except the ones listed - * above) are used for the training and prediction input. - * display_name - Output only. - * data_type - Output only. + * * name - May be set on CreateModel, if set only the columns specified are + * used, otherwise all primary table's columns (except the ones listed + * above) are used for the training and prediction input. + * * display_name - Output only. + * * data_type - Output only. * * Generated from protobuf field repeated .google.cloud.automl.v1beta1.ColumnSpec input_feature_column_specs = 3; */ @@ -70,9 +70,6 @@ class TablesModelMetadata extends \Google\Protobuf\Internal\Message * "MINIMIZE_RMSE" (default) - Minimize root-mean-squared error (RMSE). * "MINIMIZE_MAE" - Minimize mean-absolute error (MAE). * "MINIMIZE_RMSLE" - Minimize root-mean-squared log error (RMSLE). - * FORECASTING: - * "MINIMIZE_RMSE" (default) - Minimize root-mean-squared error (RMSE). - * "MINIMIZE_MAE" - Minimize mean-absolute error (MAE). * * Generated from protobuf field string optimization_objective = 4; */ @@ -116,7 +113,6 @@ class TablesModelMetadata extends \Google\Protobuf\Internal\Message * Generated from protobuf field bool disable_early_stopping = 12; */ private $disable_early_stopping = false; - protected $additional_optimization_objective_config; /** * Constructor. @@ -145,11 +141,11 @@ class TablesModelMetadata extends \Google\Protobuf\Internal\Message * [ml_use_column][google.cloud.automl.v1beta1.TablesDatasetMetadata.ml_use_column_spec_id] * must never be included here. * Only 3 fields are used: - * name - May be set on CreateModel, if set only the columns specified are - * used, otherwise all primary table's columns (except the ones listed - * above) are used for the training and prediction input. - * display_name - Output only. - * data_type - Output only. + * * name - May be set on CreateModel, if set only the columns specified are + * used, otherwise all primary table's columns (except the ones listed + * above) are used for the training and prediction input. + * * display_name - Output only. + * * data_type - Output only. * @type string $optimization_objective * Objective function the model is optimizing towards. The training process * creates a model that maximizes/minimizes the value of the objective @@ -171,15 +167,6 @@ class TablesModelMetadata extends \Google\Protobuf\Internal\Message * "MINIMIZE_RMSE" (default) - Minimize root-mean-squared error (RMSE). * "MINIMIZE_MAE" - Minimize mean-absolute error (MAE). * "MINIMIZE_RMSLE" - Minimize root-mean-squared log error (RMSLE). - * FORECASTING: - * "MINIMIZE_RMSE" (default) - Minimize root-mean-squared error (RMSE). - * "MINIMIZE_MAE" - Minimize mean-absolute error (MAE). - * @type float $optimization_objective_recall_value - * Required when optimization_objective is "MAXIMIZE_PRECISION_AT_RECALL". - * Must be between 0 and 1, inclusive. - * @type float $optimization_objective_precision_value - * Required when optimization_objective is "MAXIMIZE_RECALL_AT_PRECISION". - * Must be between 0 and 1, inclusive. * @type \Google\Cloud\AutoMl\V1beta1\TablesModelColumnInfo[]|\Google\Protobuf\Internal\RepeatedField $tables_model_column_info * Output only. Auxiliary information for each of the * input_feature_column_specs with respect to this particular model. @@ -263,11 +250,11 @@ public function setTargetColumnSpec($var) * [ml_use_column][google.cloud.automl.v1beta1.TablesDatasetMetadata.ml_use_column_spec_id] * must never be included here. * Only 3 fields are used: - * name - May be set on CreateModel, if set only the columns specified are - * used, otherwise all primary table's columns (except the ones listed - * above) are used for the training and prediction input. - * display_name - Output only. - * data_type - Output only. + * * name - May be set on CreateModel, if set only the columns specified are + * used, otherwise all primary table's columns (except the ones listed + * above) are used for the training and prediction input. + * * display_name - Output only. + * * data_type - Output only. * * Generated from protobuf field repeated .google.cloud.automl.v1beta1.ColumnSpec input_feature_column_specs = 3; * @return \Google\Protobuf\Internal\RepeatedField @@ -288,11 +275,11 @@ public function getInputFeatureColumnSpecs() * [ml_use_column][google.cloud.automl.v1beta1.TablesDatasetMetadata.ml_use_column_spec_id] * must never be included here. * Only 3 fields are used: - * name - May be set on CreateModel, if set only the columns specified are - * used, otherwise all primary table's columns (except the ones listed - * above) are used for the training and prediction input. - * display_name - Output only. - * data_type - Output only. + * * name - May be set on CreateModel, if set only the columns specified are + * used, otherwise all primary table's columns (except the ones listed + * above) are used for the training and prediction input. + * * display_name - Output only. + * * data_type - Output only. * * Generated from protobuf field repeated .google.cloud.automl.v1beta1.ColumnSpec input_feature_column_specs = 3; * @param \Google\Cloud\AutoMl\V1beta1\ColumnSpec[]|\Google\Protobuf\Internal\RepeatedField $var @@ -327,9 +314,6 @@ public function setInputFeatureColumnSpecs($var) * "MINIMIZE_RMSE" (default) - Minimize root-mean-squared error (RMSE). * "MINIMIZE_MAE" - Minimize mean-absolute error (MAE). * "MINIMIZE_RMSLE" - Minimize root-mean-squared log error (RMSLE). - * FORECASTING: - * "MINIMIZE_RMSE" (default) - Minimize root-mean-squared error (RMSE). - * "MINIMIZE_MAE" - Minimize mean-absolute error (MAE). * * Generated from protobuf field string optimization_objective = 4; * @return string @@ -360,9 +344,6 @@ public function getOptimizationObjective() * "MINIMIZE_RMSE" (default) - Minimize root-mean-squared error (RMSE). * "MINIMIZE_MAE" - Minimize mean-absolute error (MAE). * "MINIMIZE_RMSLE" - Minimize root-mean-squared log error (RMSLE). - * FORECASTING: - * "MINIMIZE_RMSE" (default) - Minimize root-mean-squared error (RMSE). - * "MINIMIZE_MAE" - Minimize mean-absolute error (MAE). * * Generated from protobuf field string optimization_objective = 4; * @param string $var @@ -376,62 +357,6 @@ public function setOptimizationObjective($var) return $this; } - /** - * Required when optimization_objective is "MAXIMIZE_PRECISION_AT_RECALL". - * Must be between 0 and 1, inclusive. - * - * Generated from protobuf field float optimization_objective_recall_value = 17; - * @return float - */ - public function getOptimizationObjectiveRecallValue() - { - return $this->readOneof(17); - } - - /** - * Required when optimization_objective is "MAXIMIZE_PRECISION_AT_RECALL". - * Must be between 0 and 1, inclusive. - * - * Generated from protobuf field float optimization_objective_recall_value = 17; - * @param float $var - * @return $this - */ - public function setOptimizationObjectiveRecallValue($var) - { - GPBUtil::checkFloat($var); - $this->writeOneof(17, $var); - - return $this; - } - - /** - * Required when optimization_objective is "MAXIMIZE_RECALL_AT_PRECISION". - * Must be between 0 and 1, inclusive. - * - * Generated from protobuf field float optimization_objective_precision_value = 18; - * @return float - */ - public function getOptimizationObjectivePrecisionValue() - { - return $this->readOneof(18); - } - - /** - * Required when optimization_objective is "MAXIMIZE_RECALL_AT_PRECISION". - * Must be between 0 and 1, inclusive. - * - * Generated from protobuf field float optimization_objective_precision_value = 18; - * @param float $var - * @return $this - */ - public function setOptimizationObjectivePrecisionValue($var) - { - GPBUtil::checkFloat($var); - $this->writeOneof(18, $var); - - return $this; - } - /** * Output only. Auxiliary information for each of the * input_feature_column_specs with respect to this particular model. @@ -566,13 +491,5 @@ public function setDisableEarlyStopping($var) return $this; } - /** - * @return string - */ - public function getAdditionalOptimizationObjectiveConfig() - { - return $this->whichOneof("additional_optimization_objective_config"); - } - } diff --git a/AutoMl/src/V1beta1/TextClassificationDatasetMetadata.php b/AutoMl/src/V1beta1/TextClassificationDatasetMetadata.php index 21fc64dcb734..45e574037d0c 100644 --- a/AutoMl/src/V1beta1/TextClassificationDatasetMetadata.php +++ b/AutoMl/src/V1beta1/TextClassificationDatasetMetadata.php @@ -16,8 +16,7 @@ class TextClassificationDatasetMetadata extends \Google\Protobuf\Internal\Message { /** - * Required. - * Type of the classification problem. + * Required. Type of the classification problem. * * Generated from protobuf field .google.cloud.automl.v1beta1.ClassificationType classification_type = 1; */ @@ -30,8 +29,7 @@ class TextClassificationDatasetMetadata extends \Google\Protobuf\Internal\Messag * Optional. Data for populating the Message object. * * @type int $classification_type - * Required. - * Type of the classification problem. + * Required. Type of the classification problem. * } */ public function __construct($data = NULL) { @@ -40,8 +38,7 @@ public function __construct($data = NULL) { } /** - * Required. - * Type of the classification problem. + * Required. Type of the classification problem. * * Generated from protobuf field .google.cloud.automl.v1beta1.ClassificationType classification_type = 1; * @return int @@ -52,8 +49,7 @@ public function getClassificationType() } /** - * Required. - * Type of the classification problem. + * Required. Type of the classification problem. * * Generated from protobuf field .google.cloud.automl.v1beta1.ClassificationType classification_type = 1; * @param int $var diff --git a/AutoMl/src/V1beta1/TextSentimentDatasetMetadata.php b/AutoMl/src/V1beta1/TextSentimentDatasetMetadata.php index 1d560404d1a9..eb9c6152a9f8 100644 --- a/AutoMl/src/V1beta1/TextSentimentDatasetMetadata.php +++ b/AutoMl/src/V1beta1/TextSentimentDatasetMetadata.php @@ -16,8 +16,7 @@ class TextSentimentDatasetMetadata extends \Google\Protobuf\Internal\Message { /** - * Required. - * A sentiment is expressed as an integer ordinal, where higher value + * Required. A sentiment is expressed as an integer ordinal, where higher value * means a more positive sentiment. The range of sentiments that will be used * is between 0 and sentiment_max (inclusive on both ends), and all the values * in the range must be represented in the dataset before a model can be @@ -35,8 +34,7 @@ class TextSentimentDatasetMetadata extends \Google\Protobuf\Internal\Message * Optional. Data for populating the Message object. * * @type int $sentiment_max - * Required. - * A sentiment is expressed as an integer ordinal, where higher value + * Required. A sentiment is expressed as an integer ordinal, where higher value * means a more positive sentiment. The range of sentiments that will be used * is between 0 and sentiment_max (inclusive on both ends), and all the values * in the range must be represented in the dataset before a model can be @@ -50,8 +48,7 @@ public function __construct($data = NULL) { } /** - * Required. - * A sentiment is expressed as an integer ordinal, where higher value + * Required. A sentiment is expressed as an integer ordinal, where higher value * means a more positive sentiment. The range of sentiments that will be used * is between 0 and sentiment_max (inclusive on both ends), and all the values * in the range must be represented in the dataset before a model can be @@ -67,8 +64,7 @@ public function getSentimentMax() } /** - * Required. - * A sentiment is expressed as an integer ordinal, where higher value + * Required. A sentiment is expressed as an integer ordinal, where higher value * means a more positive sentiment. The range of sentiments that will be used * is between 0 and sentiment_max (inclusive on both ends), and all the values * in the range must be represented in the dataset before a model can be diff --git a/AutoMl/src/V1beta1/TextSnippet.php b/AutoMl/src/V1beta1/TextSnippet.php index 716d84c32e1f..1198bb1b7006 100644 --- a/AutoMl/src/V1beta1/TextSnippet.php +++ b/AutoMl/src/V1beta1/TextSnippet.php @@ -23,9 +23,9 @@ class TextSnippet extends \Google\Protobuf\Internal\Message */ private $content = ''; /** - * The format of the source text. Currently the only two allowed values are - * "text/html" and "text/plain". If left blank the format is automatically - * determined from the type of the uploaded content. + * Optional. The format of [content][google.cloud.automl.v1beta1.TextSnippet.content]. Currently the only two allowed + * values are "text/html" and "text/plain". If left blank, the format is + * automatically determined from the type of the uploaded [content][google.cloud.automl.v1beta1.TextSnippet.content]. * * Generated from protobuf field string mime_type = 2; */ @@ -47,9 +47,9 @@ class TextSnippet extends \Google\Protobuf\Internal\Message * Required. The content of the text snippet as a string. Up to 250000 * characters long. * @type string $mime_type - * The format of the source text. Currently the only two allowed values are - * "text/html" and "text/plain". If left blank the format is automatically - * determined from the type of the uploaded content. + * Optional. The format of [content][google.cloud.automl.v1beta1.TextSnippet.content]. Currently the only two allowed + * values are "text/html" and "text/plain". If left blank, the format is + * automatically determined from the type of the uploaded [content][google.cloud.automl.v1beta1.TextSnippet.content]. * @type string $content_uri * Output only. HTTP URI where you can download the content. * } @@ -88,9 +88,9 @@ public function setContent($var) } /** - * The format of the source text. Currently the only two allowed values are - * "text/html" and "text/plain". If left blank the format is automatically - * determined from the type of the uploaded content. + * Optional. The format of [content][google.cloud.automl.v1beta1.TextSnippet.content]. Currently the only two allowed + * values are "text/html" and "text/plain". If left blank, the format is + * automatically determined from the type of the uploaded [content][google.cloud.automl.v1beta1.TextSnippet.content]. * * Generated from protobuf field string mime_type = 2; * @return string @@ -101,9 +101,9 @@ public function getMimeType() } /** - * The format of the source text. Currently the only two allowed values are - * "text/html" and "text/plain". If left blank the format is automatically - * determined from the type of the uploaded content. + * Optional. The format of [content][google.cloud.automl.v1beta1.TextSnippet.content]. Currently the only two allowed + * values are "text/html" and "text/plain". If left blank, the format is + * automatically determined from the type of the uploaded [content][google.cloud.automl.v1beta1.TextSnippet.content]. * * Generated from protobuf field string mime_type = 2; * @param string $var diff --git a/AutoMl/src/V1beta1/TypeCode.php b/AutoMl/src/V1beta1/TypeCode.php index 7eb6a7f9d9fa..84dbb8048da7 100644 --- a/AutoMl/src/V1beta1/TypeCode.php +++ b/AutoMl/src/V1beta1/TypeCode.php @@ -9,12 +9,6 @@ /** * `TypeCode` is used as a part of * [DataType][google.cloud.automl.v1beta1.DataType]. - * Each legal value of a DataType can be encoded to or decoded from a JSON - * value, using the encodings listed below, and definitions of which can be - * found at - * https: - * //developers.google.com/protocol-buffers - * // /docs/reference/google.protobuf#value. * * Protobuf type google.cloud.automl.v1beta1.TypeCode */ diff --git a/AutoMl/src/V1beta1/UpdateColumnSpecRequest.php b/AutoMl/src/V1beta1/UpdateColumnSpecRequest.php index 94f69e858bea..d6687b022e15 100644 --- a/AutoMl/src/V1beta1/UpdateColumnSpecRequest.php +++ b/AutoMl/src/V1beta1/UpdateColumnSpecRequest.php @@ -22,11 +22,7 @@ class UpdateColumnSpecRequest extends \Google\Protobuf\Internal\Message */ private $column_spec = null; /** - * The update mask applies to the resource. For the `FieldMask` definition, - * see - * https: - * //developers.google.com/protocol-buffers - * // /docs/reference/google.protobuf#fieldmask + * The update mask applies to the resource. * * Generated from protobuf field .google.protobuf.FieldMask update_mask = 2; */ @@ -41,11 +37,7 @@ class UpdateColumnSpecRequest extends \Google\Protobuf\Internal\Message * @type \Google\Cloud\AutoMl\V1beta1\ColumnSpec $column_spec * The column spec which replaces the resource on the server. * @type \Google\Protobuf\FieldMask $update_mask - * The update mask applies to the resource. For the `FieldMask` definition, - * see - * https: - * //developers.google.com/protocol-buffers - * // /docs/reference/google.protobuf#fieldmask + * The update mask applies to the resource. * } */ public function __construct($data = NULL) { @@ -80,11 +72,7 @@ public function setColumnSpec($var) } /** - * The update mask applies to the resource. For the `FieldMask` definition, - * see - * https: - * //developers.google.com/protocol-buffers - * // /docs/reference/google.protobuf#fieldmask + * The update mask applies to the resource. * * Generated from protobuf field .google.protobuf.FieldMask update_mask = 2; * @return \Google\Protobuf\FieldMask @@ -95,11 +83,7 @@ public function getUpdateMask() } /** - * The update mask applies to the resource. For the `FieldMask` definition, - * see - * https: - * //developers.google.com/protocol-buffers - * // /docs/reference/google.protobuf#fieldmask + * The update mask applies to the resource. * * Generated from protobuf field .google.protobuf.FieldMask update_mask = 2; * @param \Google\Protobuf\FieldMask $var diff --git a/AutoMl/src/V1beta1/UpdateDatasetRequest.php b/AutoMl/src/V1beta1/UpdateDatasetRequest.php index 6488f4b9f7cf..e3fb5fb6a10d 100644 --- a/AutoMl/src/V1beta1/UpdateDatasetRequest.php +++ b/AutoMl/src/V1beta1/UpdateDatasetRequest.php @@ -22,11 +22,7 @@ class UpdateDatasetRequest extends \Google\Protobuf\Internal\Message */ private $dataset = null; /** - * The update mask applies to the resource. For the `FieldMask` definition, - * see - * https: - * //developers.google.com/protocol-buffers - * // /docs/reference/google.protobuf#fieldmask + * The update mask applies to the resource. * * Generated from protobuf field .google.protobuf.FieldMask update_mask = 2; */ @@ -41,11 +37,7 @@ class UpdateDatasetRequest extends \Google\Protobuf\Internal\Message * @type \Google\Cloud\AutoMl\V1beta1\Dataset $dataset * The dataset which replaces the resource on the server. * @type \Google\Protobuf\FieldMask $update_mask - * The update mask applies to the resource. For the `FieldMask` definition, - * see - * https: - * //developers.google.com/protocol-buffers - * // /docs/reference/google.protobuf#fieldmask + * The update mask applies to the resource. * } */ public function __construct($data = NULL) { @@ -80,11 +72,7 @@ public function setDataset($var) } /** - * The update mask applies to the resource. For the `FieldMask` definition, - * see - * https: - * //developers.google.com/protocol-buffers - * // /docs/reference/google.protobuf#fieldmask + * The update mask applies to the resource. * * Generated from protobuf field .google.protobuf.FieldMask update_mask = 2; * @return \Google\Protobuf\FieldMask @@ -95,11 +83,7 @@ public function getUpdateMask() } /** - * The update mask applies to the resource. For the `FieldMask` definition, - * see - * https: - * //developers.google.com/protocol-buffers - * // /docs/reference/google.protobuf#fieldmask + * The update mask applies to the resource. * * Generated from protobuf field .google.protobuf.FieldMask update_mask = 2; * @param \Google\Protobuf\FieldMask $var diff --git a/AutoMl/src/V1beta1/UpdateTableSpecRequest.php b/AutoMl/src/V1beta1/UpdateTableSpecRequest.php index 55153a9139e5..f3e7e24f63b4 100644 --- a/AutoMl/src/V1beta1/UpdateTableSpecRequest.php +++ b/AutoMl/src/V1beta1/UpdateTableSpecRequest.php @@ -22,11 +22,7 @@ class UpdateTableSpecRequest extends \Google\Protobuf\Internal\Message */ private $table_spec = null; /** - * The update mask applies to the resource. For the `FieldMask` definition, - * see - * https: - * //developers.google.com/protocol-buffers - * // /docs/reference/google.protobuf#fieldmask + * The update mask applies to the resource. * * Generated from protobuf field .google.protobuf.FieldMask update_mask = 2; */ @@ -41,11 +37,7 @@ class UpdateTableSpecRequest extends \Google\Protobuf\Internal\Message * @type \Google\Cloud\AutoMl\V1beta1\TableSpec $table_spec * The table spec which replaces the resource on the server. * @type \Google\Protobuf\FieldMask $update_mask - * The update mask applies to the resource. For the `FieldMask` definition, - * see - * https: - * //developers.google.com/protocol-buffers - * // /docs/reference/google.protobuf#fieldmask + * The update mask applies to the resource. * } */ public function __construct($data = NULL) { @@ -80,11 +72,7 @@ public function setTableSpec($var) } /** - * The update mask applies to the resource. For the `FieldMask` definition, - * see - * https: - * //developers.google.com/protocol-buffers - * // /docs/reference/google.protobuf#fieldmask + * The update mask applies to the resource. * * Generated from protobuf field .google.protobuf.FieldMask update_mask = 2; * @return \Google\Protobuf\FieldMask @@ -95,11 +83,7 @@ public function getUpdateMask() } /** - * The update mask applies to the resource. For the `FieldMask` definition, - * see - * https: - * //developers.google.com/protocol-buffers - * // /docs/reference/google.protobuf#fieldmask + * The update mask applies to the resource. * * Generated from protobuf field .google.protobuf.FieldMask update_mask = 2; * @param \Google\Protobuf\FieldMask $var diff --git a/AutoMl/src/V1beta1/VideoObjectTrackingAnnotation.php b/AutoMl/src/V1beta1/VideoObjectTrackingAnnotation.php index da4330031d5c..4064081745f1 100644 --- a/AutoMl/src/V1beta1/VideoObjectTrackingAnnotation.php +++ b/AutoMl/src/V1beta1/VideoObjectTrackingAnnotation.php @@ -16,8 +16,7 @@ class VideoObjectTrackingAnnotation extends \Google\Protobuf\Internal\Message { /** - * Optional. - * The instance of the object, expressed as a positive integer. Used to tell + * Optional. The instance of the object, expressed as a positive integer. Used to tell * apart objects of the same type (i.e. AnnotationSpec) when multiple are * present on a single example. * NOTE: Instance ID prediction quality is not a part of model evaluation and @@ -43,8 +42,7 @@ class VideoObjectTrackingAnnotation extends \Google\Protobuf\Internal\Message */ private $bounding_box = null; /** - * Output only. - * The confidence that this annotation is positive for the video at + * Output only. The confidence that this annotation is positive for the video at * the time_offset, value in [0, 1], higher means higher positivity * confidence. For annotations created by the user the score is 1. When * user approves an annotation, the original float score is kept (and not @@ -61,8 +59,7 @@ class VideoObjectTrackingAnnotation extends \Google\Protobuf\Internal\Message * Optional. Data for populating the Message object. * * @type string $instance_id - * Optional. - * The instance of the object, expressed as a positive integer. Used to tell + * Optional. The instance of the object, expressed as a positive integer. Used to tell * apart objects of the same type (i.e. AnnotationSpec) when multiple are * present on a single example. * NOTE: Instance ID prediction quality is not a part of model evaluation and @@ -76,8 +73,7 @@ class VideoObjectTrackingAnnotation extends \Google\Protobuf\Internal\Message * Required. The rectangle representing the object location on the frame (i.e. * at the time_offset of the video). * @type float $score - * Output only. - * The confidence that this annotation is positive for the video at + * Output only. The confidence that this annotation is positive for the video at * the time_offset, value in [0, 1], higher means higher positivity * confidence. For annotations created by the user the score is 1. When * user approves an annotation, the original float score is kept (and not @@ -90,8 +86,7 @@ public function __construct($data = NULL) { } /** - * Optional. - * The instance of the object, expressed as a positive integer. Used to tell + * Optional. The instance of the object, expressed as a positive integer. Used to tell * apart objects of the same type (i.e. AnnotationSpec) when multiple are * present on a single example. * NOTE: Instance ID prediction quality is not a part of model evaluation and @@ -108,8 +103,7 @@ public function getInstanceId() } /** - * Optional. - * The instance of the object, expressed as a positive integer. Used to tell + * Optional. The instance of the object, expressed as a positive integer. Used to tell * apart objects of the same type (i.e. AnnotationSpec) when multiple are * present on a single example. * NOTE: Instance ID prediction quality is not a part of model evaluation and @@ -186,8 +180,7 @@ public function setBoundingBox($var) } /** - * Output only. - * The confidence that this annotation is positive for the video at + * Output only. The confidence that this annotation is positive for the video at * the time_offset, value in [0, 1], higher means higher positivity * confidence. For annotations created by the user the score is 1. When * user approves an annotation, the original float score is kept (and not @@ -202,8 +195,7 @@ public function getScore() } /** - * Output only. - * The confidence that this annotation is positive for the video at + * Output only. The confidence that this annotation is positive for the video at * the time_offset, value in [0, 1], higher means higher positivity * confidence. For annotations created by the user the score is 1. When * user approves an annotation, the original float score is kept (and not diff --git a/AutoMl/synth.metadata b/AutoMl/synth.metadata index 5927d3617db1..8e964110ee31 100644 --- a/AutoMl/synth.metadata +++ b/AutoMl/synth.metadata @@ -1,5 +1,5 @@ { - "updateTime": "2019-08-07T19:24:02.900108Z", + "updateTime": "2019-08-10T09:58:50.644477Z", "sources": [ { "generator": { @@ -12,8 +12,8 @@ "git": { "name": "googleapis", "remote": "https://github.com/googleapis/googleapis.git", - "sha": "3a1b46a6668194a527e532a2c355b404c79b0e6a", - "internalRef": "262167956" + "sha": "2a2c5518f64010c4e458afc818e57ed24fecdf6d", + "internalRef": "262646243" } } ], diff --git a/AutoMl/tests/Unit/V1beta1/AutoMlClientTest.php b/AutoMl/tests/Unit/V1beta1/AutoMlClientTest.php index 626f0f2f3bb0..3c69510d790e 100644 --- a/AutoMl/tests/Unit/V1beta1/AutoMlClientTest.php +++ b/AutoMl/tests/Unit/V1beta1/AutoMlClientTest.php @@ -2109,12 +2109,14 @@ public function getTableSpecTest() $name2 = 'name2-1052831874'; $timeColumnSpecId = 'timeColumnSpecId1558734824'; $rowCount = 1340416618; + $validRowCount = 406068761; $columnCount = 122671386; $etag = 'etag3123477'; $expectedResponse = new TableSpec(); $expectedResponse->setName($name2); $expectedResponse->setTimeColumnSpecId($timeColumnSpecId); $expectedResponse->setRowCount($rowCount); + $expectedResponse->setValidRowCount($validRowCount); $expectedResponse->setColumnCount($columnCount); $expectedResponse->setEtag($etag); $transport->addResponse($expectedResponse); @@ -2269,12 +2271,14 @@ public function updateTableSpecTest() $name = 'name3373707'; $timeColumnSpecId = 'timeColumnSpecId1558734824'; $rowCount = 1340416618; + $validRowCount = 406068761; $columnCount = 122671386; $etag = 'etag3123477'; $expectedResponse = new TableSpec(); $expectedResponse->setName($name); $expectedResponse->setTimeColumnSpecId($timeColumnSpecId); $expectedResponse->setRowCount($rowCount); + $expectedResponse->setValidRowCount($validRowCount); $expectedResponse->setColumnCount($columnCount); $expectedResponse->setEtag($etag); $transport->addResponse($expectedResponse);