| /* Copyright 2015 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. |
| ==============================================================================*/ |
| |
| // See docs in ../ops/io_ops.cc |
| #include "tensorflow/core/kernels/save_restore_tensor.h" |
| |
| #include "tensorflow/core/framework/op_kernel.h" |
| #include "tensorflow/core/framework/types.h" |
| #include "tensorflow/core/lib/gtl/array_slice.h" |
| #include "tensorflow/core/lib/strings/stringprintf.h" |
| #include "tensorflow/core/platform/logging.h" |
| #include "tensorflow/core/platform/types.h" |
| #include "tensorflow/core/util/tensor_slice_writer.h" |
| |
| namespace tensorflow { |
| |
| class SaveOp : public OpKernel { |
| public: |
| explicit SaveOp(OpKernelConstruction* context) : OpKernel(context) {} |
| |
| void Compute(OpKernelContext* context) override { |
| SaveTensors(context, &checkpoint::CreateTableTensorSliceBuilder, false); |
| } |
| }; |
| |
| REGISTER_KERNEL_BUILDER(Name("Save").Device(DEVICE_CPU), SaveOp); |
| |
| class SaveSlicesOp : public OpKernel { |
| public: |
| explicit SaveSlicesOp(OpKernelConstruction* context) : OpKernel(context) {} |
| |
| void Compute(OpKernelContext* context) override { |
| SaveTensors(context, &checkpoint::CreateTableTensorSliceBuilder, true); |
| } |
| }; |
| |
| REGISTER_KERNEL_BUILDER(Name("SaveSlices").Device(DEVICE_CPU), SaveSlicesOp); |
| |
| class ShardedFilenameOp : public OpKernel { |
| public: |
| explicit ShardedFilenameOp(OpKernelConstruction* ctx) : OpKernel(ctx) {} |
| |
| void Compute(OpKernelContext* ctx) override { |
| static const char* input_names[3] = {"basename", "shard", "num_shards"}; |
| for (int i = 0; i < ctx->num_inputs(); ++i) { |
| OP_REQUIRES(ctx, IsLegacyScalar(ctx->input(i).shape()), |
| errors::InvalidArgument(input_names[i], |
| " must be a scalar, got shape ", |
| ctx->input(i).shape().DebugString())); |
| } |
| Tensor* out = nullptr; |
| OP_REQUIRES_OK(ctx, ctx->allocate_output(0, TensorShape({}), &out)); |
| out->scalar<string>()() = strings::Printf( |
| "%s-%05d-of-%05d", ctx->input(0).scalar<string>()().c_str(), |
| ctx->input(1).scalar<int32>()(), ctx->input(2).scalar<int32>()()); |
| } |
| }; |
| |
| REGISTER_KERNEL_BUILDER(Name("ShardedFilename").Device(DEVICE_CPU), |
| ShardedFilenameOp); |
| |
| class ShardedFilespecOp : public OpKernel { |
| public: |
| explicit ShardedFilespecOp(OpKernelConstruction* ctx) : OpKernel(ctx) {} |
| |
| void Compute(OpKernelContext* ctx) override { |
| static const char* input_names[2] = {"basename", "num_shards"}; |
| for (int i = 0; i < ctx->num_inputs(); ++i) { |
| OP_REQUIRES(ctx, IsLegacyScalar(ctx->input(i).shape()), |
| errors::InvalidArgument(input_names[i], |
| " must be a scalar, got shape ", |
| ctx->input(i).shape().DebugString())); |
| } |
| Tensor* out = nullptr; |
| OP_REQUIRES_OK(ctx, ctx->allocate_output(0, TensorShape({}), &out)); |
| out->scalar<string>()() = strings::Printf( |
| "%s-\?\?\?\?\?-of-%05d", ctx->input(0).scalar<string>()().c_str(), |
| ctx->input(1).scalar<int32>()()); |
| } |
| }; |
| REGISTER_KERNEL_BUILDER(Name("ShardedFilespec").Device(DEVICE_CPU), |
| ShardedFilespecOp); |
| |
| } // namespace tensorflow |