17b63987e5
Conv1D.__call__ overhead by 15% Removes the indirection caused by using the nn_ops.Convolution class rather than nn_ops.convolution. PiperOrigin-RevId: 315920158 Change-Id: Ia5db49a36870b424b70d9d04962b84697d89bf55
123 lines
4.1 KiB
Python
123 lines
4.1 KiB
Python
# Copyright 2017 The TensorFlow Authors. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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# ==============================================================================
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"""Tests for Convolution node name match via the XLA JIT.
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The canned results in these tests are created by running each test using the
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Tensorflow CPU device and saving the output.
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"""
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from __future__ import absolute_import
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from __future__ import division
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from __future__ import print_function
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import numpy as np
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from tensorflow.compiler.tests import xla_test
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from tensorflow.python.framework import ops
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from tensorflow.python.layers import layers
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from tensorflow.python.ops import array_ops
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from tensorflow.python.ops import control_flow_ops
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from tensorflow.python.platform import googletest
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class ConvolutionNodeNameTest(xla_test.XLATestCase):
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"""Verify convolution node name match.
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Verify convolution node names on TPU and CPU match with dilation > 1.
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"""
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def _verifyNodeNameMatch(self, layer, input_sizes, filter_sizes, strides,
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dilations):
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def _GetNodeNames(use_xla):
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with self.session():
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input_tensor = array_ops.placeholder(np.float32, shape=input_sizes)
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if use_xla:
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with self.test_scope():
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# pylint: disable=protected-access
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graph = ops.get_default_graph()
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graph._set_control_flow_context(
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control_flow_ops.XLAControlFlowContext())
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# pylint: enable=protected-access
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conv2d_op = layer(
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filters=64,
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kernel_size=filter_sizes,
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dilation_rate=dilations,
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padding="same")
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_ = conv2d_op(input_tensor)
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return [n.name for n in ops.get_default_graph().as_graph_def().node]
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else:
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with ops.device("CPU"):
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conv2d_op = layer(
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filters=64,
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kernel_size=filter_sizes,
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dilation_rate=dilations,
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padding="same")
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_ = conv2d_op(input_tensor)
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names = [
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n.name for n in ops.get_default_graph().as_graph_def().node
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]
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# filter out space to depth ops.
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return [
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name for name in names
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if "space" not in name and "Space" not in name
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]
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xla_names = _GetNodeNames(use_xla=True)
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no_xla_names = _GetNodeNames(use_xla=False)
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# CPU path creates some additional nodes to handle dilations.
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# TODO(b/138804006): Remove this when CPU & GPU support dilations.
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filtered_no_xla_names = []
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for name in no_xla_names:
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if ("dilation_rate" in name or "filter_shape" in name or "stack" in name):
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continue
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else:
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filtered_no_xla_names.append(name)
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self.assertListEqual(xla_names, filtered_no_xla_names)
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def testConv1DNodeNameMatch(self):
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input_sizes = [8, 16, 3]
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filter_sizes = [7]
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strides = 1
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dilations = [2]
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layer = layers.Conv1D
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self._verifyNodeNameMatch(layer, input_sizes, filter_sizes, strides,
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dilations)
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def testConv2DNodeNameMatch(self):
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input_sizes = [8, 16, 16, 3]
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filter_sizes = [7, 7]
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strides = 1
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dilations = [2, 2]
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layer = layers.Conv2D
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self._verifyNodeNameMatch(layer, input_sizes, filter_sizes, strides,
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dilations)
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def testConv3DNodeNameMatch(self):
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input_sizes = [8, 16, 16, 16, 3]
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filter_sizes = [7, 7, 7]
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strides = 1
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dilations = [2, 2, 2]
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layer = layers.Conv3D
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self._verifyNodeNameMatch(layer, input_sizes, filter_sizes, strides,
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dilations)
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if __name__ == "__main__":
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googletest.main()
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