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| /* Copyright 2017 The TensorFlow Authors. All Rights Reserved. | ||
| Licensed under the Apache License, Version 2.0 (the "License"); | ||
| you may not use this file except in compliance with the License. | ||
| You may obtain a copy of the License at | ||
| http://www.apache.org/licenses/LICENSE-2.0 | ||
| Unless required by applicable law or agreed to in writing, software | ||
| distributed under the License is distributed on an "AS IS" BASIS, | ||
| WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | ||
| See the License for the specific language governing permissions and | ||
| limitations under the License. | ||
| ==============================================================================*/ | ||
|
|
||
| #include "tensorflow/core/grappler/costs/utils.h" | ||
| #include "tensorflow/core/framework/graph.pb.h" | ||
| #include "tensorflow/core/framework/node_def_builder.h" | ||
| #include "tensorflow/core/framework/op_kernel.h" | ||
| #include "tensorflow/core/framework/tensor.h" | ||
| #include "tensorflow/core/framework/tensor_testutil.h" | ||
| #include "tensorflow/core/framework/types.h" | ||
| #include "tensorflow/core/framework/types.pb.h" | ||
| #include "tensorflow/core/platform/test.h" | ||
|
|
||
| namespace tensorflow { | ||
| namespace grappler { | ||
|
|
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| class UtilsTest : public ::testing::Test { | ||
| public: | ||
| void CreateConstOp(const string& name, std::initializer_list<int64> dims, | ||
| NodeDef* node) { | ||
| Tensor tensor(DT_FLOAT, TensorShape(dims)); | ||
| for (int64 i = 0; i < tensor.NumElements(); ++i) { | ||
| tensor.flat<float>()(i) = i / 10.0f; | ||
| } | ||
| TF_CHECK_OK(NodeDefBuilder(name, "Const") | ||
| .Attr("dtype", DT_FLOAT) | ||
| .Attr("value", tensor) | ||
| .Finalize(node)); | ||
| } | ||
|
|
||
| void CreateConstSizesOp(const string& name, const std::vector<int32>& sizes, | ||
| NodeDef* node) { | ||
| TensorShape shape; | ||
| shape.AddDim(sizes.size()); | ||
| Tensor tensor(DT_INT32, shape); | ||
| for (int64 i = 0; i < tensor.NumElements(); ++i) { | ||
| tensor.flat<int32>()(i) = sizes[i]; | ||
| } | ||
| TF_CHECK_OK(NodeDefBuilder(name, "Const") | ||
| .Attr("dtype", DT_INT32) | ||
| .Attr("value", tensor) | ||
| .Finalize(node)); | ||
| } | ||
| }; | ||
|
|
||
| TEST_F(UtilsTest, ConvOpInfo) { | ||
| int batch = 32; | ||
| int rows = 7; | ||
| int cols = 9; | ||
| int filter_rows = 3; | ||
| int filter_cols = 3; | ||
| int out_rows = 7; | ||
| int out_cols = 9; | ||
| int in_depth = 3; | ||
| int out_depth = 5; | ||
| int stride = 1; | ||
|
|
||
| std::unordered_map<string, const NodeDef*> name_to_node; | ||
| GraphDef graph; | ||
| NodeDef* input = graph.add_node(); | ||
| name_to_node["input"] = input; | ||
| CreateConstOp("input", {batch, rows, cols, in_depth}, input); | ||
| NodeDef* filter = graph.add_node(); | ||
| name_to_node["filter"] = filter; | ||
| CreateConstOp("filter", {filter_rows, filter_cols, in_depth, out_depth}, | ||
| filter); | ||
| NodeDef* output_backprop = graph.add_node(); | ||
| name_to_node["output_backprop"] = output_backprop; | ||
| CreateConstOp("output_backprop", {batch, out_rows, out_cols, out_depth}, | ||
| output_backprop); | ||
| NodeDef* input_sizes = graph.add_node(); | ||
| name_to_node["input_sizes"] = input; | ||
| CreateConstSizesOp("input_sizes", | ||
| std::vector<int32>({batch, rows, cols, in_depth}), | ||
| input_sizes); | ||
| NodeDef* filter_sizes = graph.add_node(); | ||
| name_to_node["filter_sizes"] = filter_sizes; | ||
| CreateConstSizesOp( | ||
| "filter_sizes", | ||
| std::vector<int32>({filter_rows, filter_cols, in_depth, out_depth}), | ||
| filter_sizes); | ||
|
|
||
| TensorShape paddings_shape({4, 2}); | ||
| Tensor paddings_tensor(DT_INT32, paddings_shape); | ||
| for (int64 i = 0; i < paddings_tensor.NumElements(); ++i) { | ||
| paddings_tensor.flat<int32>()(i) = 0; | ||
| } | ||
| TF_CHECK_OK(NodeDefBuilder("paddings", "Const") | ||
| .Attr("dtype", DT_INT32) | ||
| .Attr("value", paddings_tensor) | ||
| .Finalize(graph.add_node())); | ||
|
|
||
| // Now add the convolution op | ||
| NodeDef* conv = graph.add_node(); | ||
| TF_CHECK_OK(NodeDefBuilder("conv2d", "Conv2D") | ||
| .Input("input", 0, DT_FLOAT) | ||
| .Input("filter", 0, DT_FLOAT) | ||
| .Attr("strides", {1, stride, stride, 1}) | ||
| .Attr("padding", "SAME") | ||
| .Finalize(conv)); | ||
|
|
||
| NodeDef* conv_bp_in = graph.add_node(); | ||
| TF_CHECK_OK(NodeDefBuilder("conv2d_bp_in", "Conv2DBackpropInput") | ||
| .Input("input_sizes", 0, DT_INT32) | ||
| .Input("filter", 0, DT_FLOAT) | ||
| .Input("output_backprop", 0, DT_FLOAT) | ||
| .Attr("strides", {1, stride, stride, 1}) | ||
| .Attr("padding", "SAME") | ||
| .Finalize(conv_bp_in)); | ||
|
|
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| NodeDef* conv_bp_filter = graph.add_node(); | ||
| TF_CHECK_OK(NodeDefBuilder("conv2d_bp_filter", "Conv2DBackpropFilter") | ||
| .Input("input", 0, DT_FLOAT) | ||
| .Input("filter_sizes", 0, DT_INT32) | ||
| .Input("output_backprop", 0, DT_FLOAT) | ||
| .Attr("strides", {1, stride, stride, 1}) | ||
| .Attr("padding", "SAME") | ||
| .Finalize(conv_bp_filter)); | ||
|
|
||
| for (const auto& node : graph.node()) { | ||
| if (node.name().find("conv2d") != 0) { | ||
| continue; | ||
| } | ||
| std::vector<OpInfo::TensorProperties> inputs; | ||
| inputs.resize(node.input_size()); | ||
| OpInfo info = BuildOpInfoWithoutDevice(node, name_to_node, inputs); | ||
| if (node.name() == "conv2d") { | ||
| EXPECT_EQ(2, info.inputs_size()); | ||
| } else if (node.name() == "conv2dbp_in") { | ||
| EXPECT_EQ(3, info.inputs_size()); | ||
| } else if (node.name() == "conv2d_bp_filter") { | ||
| EXPECT_EQ(3, info.inputs_size()); | ||
| } | ||
| } | ||
| } | ||
|
|
||
| } // end namespace grappler | ||
| } // end namespace tensorflow |