[Python API] Support of FP16 blobs

openvinotoolkit · Jan 27, 2021 · 0c869a3 · 0c869a3
1 parent 344494a
commit 0c869a3
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Showing 2 changed files with 17 additions and 4 deletions.
diff --git a/inference-engine/ie_bridges/python/src/openvino/inference_engine/ie_api.pyx b/inference-engine/ie_bridges/python/src/openvino/inference_engine/ie_api.pyx
@@ -173,7 +173,10 @@ cdef class Blob:
                 fp64_array_memview = self._array_data
                 self._ptr = C.make_shared_blob[double](c_tensor_desc, &fp64_array_memview[0], fp64_array_memview.shape[0])
             elif precision == "FP16":
-                raise RuntimeError("Currently, it's impossible to set_blob with FP16 precision")
+                ar = np.short(self._array_data)
+                I16_array_memview = ar
+                #I16_array_memview = self._array_data
+                self._ptr = C.make_shared_blob[int16_t](c_tensor_desc, &I16_array_memview[0], I16_array_memview.shape[0])
             elif precision == "I16":
                 I16_array_memview = self._array_data
                 self._ptr = C.make_shared_blob[int16_t](c_tensor_desc, &I16_array_memview[0], I16_array_memview.shape[0])
@@ -203,10 +206,14 @@ cdef class Blob:
     ## Blob's memory as numpy.ndarray representation
     @property
     def buffer(self):
+        print("zdes")
         representation_shape = self._initial_shape if self._initial_shape is not None else []
         cdef BlobBuffer buffer = BlobBuffer()
         buffer.reset(self._ptr, representation_shape)
-        return buffer.to_numpy()
+        print("after_reset")
+        l = buffer.to_numpy()
+        print("before return")
+        return  l
 
     ## TensorDesc of created Blob
     @property
@@ -1443,6 +1450,7 @@ cdef class BlobBuffer:
     """Copy-less accessor for Inference Engine Blob"""
 
     cdef reset(self, CBlob.Ptr & ptr, vector[size_t] representation_shape = []):
+        print("reset")
         self.ptr = ptr
         cdef CTensorDesc desc = deref(ptr).getTensorDesc()
         cdef SizeVector shape
@@ -1466,9 +1474,11 @@ cdef class BlobBuffer:
 
         self.total_stride = total_stride
         self.format = self._get_blob_format(desc)
+        print(self.format)
         self.item_size = itemsize
 
     def __getbuffer__(self, Py_buffer *buffer, int flags):
+        print("get_buf", "flags", flags)
         buffer.buf = C.get_buffer[char](deref(self.ptr))
         buffer.format = self.format
         buffer.internal = NULL
@@ -1482,6 +1492,7 @@ cdef class BlobBuffer:
         buffer.suboffsets = NULL
 
     cdef char*_get_blob_format(self, const CTensorDesc & desc):
+        print("get_blob_format")
         cdef Precision precision = desc.getPrecision()
         name = bytes(precision.name()).decode()
         # todo: half floats
@@ -1504,4 +1515,6 @@ cdef class BlobBuffer:
         return precision_to_format[name].encode()
 
     def to_numpy(self):
-        return np.asarray(self)
+        f = np.asarray(self)
+        print("to_numpy", f)
+        return f
diff --git a/inference-engine/ie_bridges/python/tests/test_Blob.py b/inference-engine/ie_bridges/python/tests/test_Blob.py
@@ -55,13 +55,13 @@ def test_write_to_buffer_fp64():
     assert np.array_equal(blob.buffer, ones_arr)
 
 
-@pytest.mark.skip(reason="Need to figure out how to implement right conversion")
 def test_write_to_buffer_fp16():
     tensor_desc = TensorDesc("FP16", [1, 3, 127, 127], "NCHW")
     array = np.zeros(shape=(1, 3, 127, 127), dtype=np.float16)
     blob = Blob(tensor_desc, array)
     ones_arr = np.ones(shape=(1, 3, 127, 127), dtype=np.float16)
     blob.buffer[:] = ones_arr
+    blob.buffer[:] = array
     assert np.array_equal(blob.buffer, ones_arr)