def testNHWCToNCHW2D(self):
x_val = [[7, 4], [9, 3], [4, 5], [5, 1]]
x = constant_op.constant(x_val)
y = nn_ops.data_format_vec_permute(x)
with self.test_session(use_gpu=test_lib.is_gpu_available()) as sess:
y_val = sess.run(y)
self.assertAllEqual(y_val, [[7, 4], [5, 1], [9, 3], [4, 5]])
def testHWNCToNHWC2D(self):
x_val = [[7, 4], [9, 3], [4, 5], [5, 1]]
x = constant_op.constant(x_val)
y = nn_ops.data_format_vec_permute(x, src_format="HWNC", dst_format="NHWC")
with self.session(use_gpu=test_lib.is_gpu_available()) as sess:
y_val = sess.run(y)
self.assertAllEqual(y_val, [[4, 5], [7, 4], [9, 3], [5, 1]])
def testNCHWToNHWC(self):
x_val = [7, 4, 9, 3]
x = constant_op.constant(x_val)
y = nn_ops.data_format_vec_permute(x, src_format="NCHW", dst_format="NHWC")
with self.test_session(use_gpu=test_lib.is_gpu_available()) as sess:
y_val = sess.run(y)
self.assertAllEqual(y_val, [7, 9, 3, 4])
def testNCHWToNHWC2D(self):
x_val = [[7, 4], [9, 3], [4, 5], [5, 1]]
x = constant_op.constant(x_val)
y = nn_ops.data_format_vec_permute(x, src_format="NCHW", dst_format="NHWC")
with test_util.use_gpu():
y_val = self.evaluate(y)
self.assertAllEqual(y_val, [[7, 4], [4, 5], [5, 1], [9, 3]])
def testNHWCToNCHW(self):
x_val = [7, 4, 9, 3]
x = constant_op.constant(x_val)
y = nn_ops.data_format_vec_permute(x)
with self.session(use_gpu=test_lib.is_gpu_available()) as sess:
y_val = sess.run(y)
self.assertAllEqual(y_val, [7, 3, 4, 9])
def testNHWCToNCHW(self):
x_val = [7, 4, 9, 3]
x = constant_op.constant(x_val)
y = nn_ops.data_format_vec_permute(x)
with test_util.use_gpu():
y_val = self.evaluate(y)
self.assertAllEqual(y_val, [7, 3, 4, 9])
def testHWNCToNHWC(self):
x_val = [7, 4, 9, 3]
x = constant_op.constant(x_val)
y = nn_ops.data_format_vec_permute(x, src_format="HWNC", dst_format="NHWC")
with test_util.use_gpu():
y_val = self.evaluate(y)
self.assertAllEqual(y_val, [9, 7, 4, 3])
def testHWNCToNHWC(self):
x_val = [7, 4, 9, 3]
x = constant_op.constant(x_val)
y = nn_ops.data_format_vec_permute(x, src_format="HWNC", dst_format="NHWC")
with test_util.use_gpu():
y_val = self.evaluate(y)
self.assertAllEqual(y_val, [9, 7, 4, 3])
def testNCHWToNHWC2D(self):
x_val = [[7, 4], [9, 3], [4, 5], [5, 1]]
x = constant_op.constant(x_val)
y = nn_ops.data_format_vec_permute(x, src_format="NCHW", dst_format="NHWC")
with test_util.use_gpu():
y_val = self.evaluate(y)
self.assertAllEqual(y_val, [[7, 4], [4, 5], [5, 1], [9, 3]])
def testNHWCToNCHW(self):
x_val = [7, 4, 9, 3]
x = constant_op.constant(x_val)
y = nn_ops.data_format_vec_permute(x)
with test_util.use_gpu():
y_val = self.evaluate(y)
self.assertAllEqual(y_val, [7, 3, 4, 9])
def test(self):
x_val = [7, 4, 9, 3]
x = constant_op.constant(x_val)
y = nn_ops.data_format_vec_permute(x)
with self.test_session(use_gpu=test_lib.is_gpu_available()) as sess:
y_val = sess.run(y)
self.assertAllEqual(y_val, [7, 3, 4, 9])
def testHWNCToNHWC2D(self):
x_val = [[7, 4], [9, 3], [4, 5], [5, 1]]
x = constant_op.constant(x_val)
y = nn_ops.data_format_vec_permute(x, src_format="HWNC", dst_format="NHWC")
with self.session(use_gpu=test_lib.is_gpu_available()) as sess:
y_val = sess.run(y)
self.assertAllEqual(y_val, [[4, 5], [7, 4], [9, 3], [5, 1]])
def _runPermuteAndCompare(self, x, src_format, dst_format, expected):
with self.cached_session() as session:
with self.test_scope():
placeholder = array_ops.placeholder(dtypes.as_dtype(x.dtype), x.shape)
param = {placeholder: x}
output = nn_ops.data_format_vec_permute(
placeholder, src_format=src_format, dst_format=dst_format)
result = session.run(output, param)
self.assertAllEqual(result, expected)
def run(self, x):
q = x + 1
q_shape = array_ops.shape(q)
# Add an OP that is not supported by TF-TRT. This allows TF-TRT to build
# two engines. The first engine produces an int32 output and the second
# engines has an int32 input and an int32 output.
q = nn_ops.data_format_vec_permute(
q_shape, src_format="NHWC", dst_format="NCHW")
q = q * 2
return array_ops.identity(q, name="output")
