Skip to content

Commit

Permalink
[NNVM][FRONTEND] Frontend testcase.
Browse files Browse the repository at this point in the history
  • Loading branch information
@srkreddy1238
srkreddy1238 committed Jun 13, 2018
1 parent 428da66 commit 2079485
Showing 1 changed file with 31 additions and 32 deletions.
63 changes: 31 additions & 32 deletions nnvm/tests/python/frontend/tensorflow/test_forward.py
View file
Original file line number Diff line number Diff line change
Expand Up @@ -73,7 +73,7 @@ def run_tf_graph(sess, input_data, input_node, output_node):
#######################################################################
# Pooling
# -------
def test_pooling(input_shape, **kwargs):
def _test_pooling(input_shape, **kwargs):
""" One iteration of pool operation with given shapes and attributes """

x = -np.arange(
Expand Down Expand Up @@ -109,26 +109,26 @@ def test_pooling(input_shape, **kwargs):
def test_forward_pooling():
""" Pooling """

test_pooling(input_shape=[2, 9, 10, 2],
_test_pooling(input_shape=[2, 9, 10, 2],
window_shape=[1, 1],
padding='SAME',
pooling_type='MAX',
dilation_rate=[1, 1],
strides=[1, 1])

test_pooling(input_shape=[2, 9, 10, 2],
_test_pooling(input_shape=[2, 9, 10, 2],
window_shape=[1, 1],
padding='SAME',
pooling_type='AVG',
dilation_rate=[1, 1],
strides=[1, 1])
test_pooling(input_shape=[2, 10, 9, 2],
_test_pooling(input_shape=[2, 10, 9, 2],
window_shape=[1, 1],
padding='SAME',
pooling_type='MAX',
dilation_rate=[1, 1],
strides=[1, 1])
test_pooling(input_shape=[2, 10, 9, 2],
_test_pooling(input_shape=[2, 10, 9, 2],
window_shape=[1, 1],
padding='SAME',
pooling_type='AVG',
Expand All @@ -139,8 +139,8 @@ def test_forward_pooling():
# Convolution
# -----------

def test_convolution(tensor_in_sizes, filter_in_sizes,
dilations, strides, padding, data_format):
def _test_convolution(tensor_in_sizes, filter_in_sizes,
dilations, strides, padding, data_format):
""" One iteration of convolution with given shapes and attributes """

total_size_1 = 1
Expand Down Expand Up @@ -186,16 +186,16 @@ def test_convolution(tensor_in_sizes, filter_in_sizes,
sess.close()

def test_forward_convolution():
test_convolution([4, 8, 8, 176], [1, 1, 176, 32], [1, 1], [1, 1], 'SAME', 'NHWC')
test_convolution([4, 17, 17, 19], [3, 3, 19, 19], [1, 1], [2, 2], 'VALID', 'NHWC')
test_convolution([4, 17, 17, 124], [1, 1, 124, 19], [1, 1], [1, 1], 'SAME', 'NHWC')
test_convolution([4, 17, 17, 12], [3, 3, 12, 32], [1, 1], [2, 2], 'VALID', 'NHWC')
_test_convolution([4, 8, 8, 176], [1, 1, 176, 32], [1, 1], [1, 1], 'SAME', 'NHWC')
_test_convolution([4, 17, 17, 19], [3, 3, 19, 19], [1, 1], [2, 2], 'VALID', 'NHWC')
_test_convolution([4, 17, 17, 124], [1, 1, 124, 19], [1, 1], [1, 1], 'SAME', 'NHWC')
_test_convolution([4, 17, 17, 12], [3, 3, 12, 32], [1, 1], [2, 2], 'VALID', 'NHWC')

#######################################################################
# Reshape
# -------

def test_reshape(data, out_shape):
def _test_reshape(data, out_shape):
""" One iteration of reshape operation with given data and out shape """

with tf.Graph().as_default():
Expand Down Expand Up @@ -223,16 +223,16 @@ def test_reshape(data, out_shape):
sess.close()

def test_forward_reshape():
test_reshape(np.arange(6.0), [2, 3])
test_reshape(np.arange(6), [-1, 2])
test_reshape(np.arange(6), [3, -1])
test_reshape(np.arange(6), [-1])
_test_reshape(np.arange(6.0), [2, 3])
_test_reshape(np.arange(6), [-1, 2])
_test_reshape(np.arange(6), [3, -1])
_test_reshape(np.arange(6), [-1])

#######################################################################
# Squeeze
# -------

def test_squeeze(data, squeeze_dims=None):
def _test_squeeze(data, squeeze_dims=None):
""" One iteration of squeeze """

if squeeze_dims is None:
Expand Down Expand Up @@ -269,30 +269,30 @@ def test_forward_squeeze():
""" Squeeze """

# Nothing to squeeze.
test_squeeze(np.arange(2).reshape((2)))
test_squeeze(np.arange(6).reshape((2, 3)))
_test_squeeze(np.arange(2).reshape((2)))
_test_squeeze(np.arange(6).reshape((2, 3)))

# Squeeze the middle element away.
test_squeeze(np.arange(4).reshape((2, 1, 2)))
_test_squeeze(np.arange(4).reshape((2, 1, 2)))

# Squeeze on both ends.
test_squeeze(np.arange(6).reshape((1, 2, 1, 3, 1)))
_test_squeeze(np.arange(6).reshape((1, 2, 1, 3, 1)))

# Positive squeeze dim index.
test_squeeze(np.arange(6).reshape((1, 2, 1, 3, 1)), [0])
test_squeeze(np.arange(6).reshape((1, 2, 1, 3, 1)), [2, 4])
test_squeeze(np.arange(6).reshape((1, 2, 1, 3, 1)), [0, 4, 2])
_test_squeeze(np.arange(6).reshape((1, 2, 1, 3, 1)), [0])
_test_squeeze(np.arange(6).reshape((1, 2, 1, 3, 1)), [2, 4])
_test_squeeze(np.arange(6).reshape((1, 2, 1, 3, 1)), [0, 4, 2])

# Negative squeeze dim index.
test_squeeze(np.arange(6).reshape((1, 2, 1, 3, 1)), [-1])
test_squeeze(np.arange(6).reshape((1, 2, 1, 3, 1)), [-3, -5])
test_squeeze(np.arange(6).reshape((1, 2, 1, 3, 1)), [-3, -5, -1])
_test_squeeze(np.arange(6).reshape((1, 2, 1, 3, 1)), [-1])
_test_squeeze(np.arange(6).reshape((1, 2, 1, 3, 1)), [-3, -5])
_test_squeeze(np.arange(6).reshape((1, 2, 1, 3, 1)), [-3, -5, -1])

#######################################################################
# ConcatV2
# --------

def test_concat_v2(data, dim):
def _test_concat_v2(data, dim):
""" One iteration of ConcatV2 """

with tf.Graph().as_default():
Expand All @@ -319,15 +319,15 @@ def test_concat_v2(data, dim):

sess.close()

def test_forward_concat_v2():
def _test_forward_concat_v2():
t1 = np.array([])
t2 = np.array([])
test_concat_v2([t1, t2], 0)

t1 = np.array([[1, 2, 3], [4, 5, 6]])
t2 = np.array([[7, 8, 9], [10, 11, 12]])

test_concat_v2([t1, t2], 1)
_test_concat_v2([t1, t2], 1)

#######################################################################
# Multi Input to graph
Expand Down Expand Up @@ -415,8 +415,7 @@ def test_forward_inception_v1():
test_forward_reshape()
test_forward_squeeze()
if tf.__version__ == '1.4.1':
test_forward_concat_v2()
_test_forward_concat_v2()
test_forward_multi_input()

test_forward_inception_v3()
test_forward_inception_v1()

0 comments on commit 2079485

Please sign in to comment.