diff options
| author |  Mingsheng Hong <hongm@google.com> | 2018-03-26 10:51:21 -0700 |
|---|---|---|
| committer |  TensorFlower Gardener <gardener@tensorflow.org> | 2018-03-26 10:53:46 -0700 |
| commit | be917027e37c5e8f21f6ba07f24bdbf072cf6dfd (patch) | |
| tree | 3df042f7c47099bac18f446f5a5719ab2424e268 /tensorflow/c/c_api_experimental.cc | |
| parent | cc6b2ae837e9c0ce3678671ff5bd59f0f8e53e06 (diff) | |
Added experimental C APIs to build a stack of dataset + iterator nodes that
reads imagenet TFRecord files.
PiperOrigin-RevId: 190488817
Diffstat (limited to 'tensorflow/c/c_api_experimental.cc')
| -rw-r--r-- | tensorflow/c/c_api_experimental.cc | 7132 |
1 files changed, 7027 insertions, 105 deletions
diff --git a/tensorflow/c/c_api_experimental.cc b/tensorflow/c/c_api_experimental.cc index 8593a8eb50..1c809cb21e 100644 --- a/tensorflow/c/c_api_experimental.cc +++ b/tensorflow/c/c_api_experimental.cc @@ -22,10 +22,15 @@ limitations under the License. #include "tensorflow/core/lib/strings/strcat.h" #include "tensorflow/core/protobuf/config.pb.h" +using tensorflow::FunctionDef; using tensorflow::Node; using tensorflow::NodeBuilder; using tensorflow::Status; -using tensorflow::Tensor; + +namespace { +typedef std::unique_ptr<TF_Function, decltype(&TF_DeleteFunction)> + UniqueFuncPtr; +} // struct TF_Operation { tensorflow::Node node; }; static TF_Operation* ToTF_Operation(Node* node) { @@ -102,8 +107,7 @@ void TF_ShutdownTPU(TF_Session* session, TF_Status* status) { /*run_metadata*/ nullptr, status); } -TF_CAPI_EXPORT extern const char* TF_GraphDebugString(TF_Graph* graph, - size_t* len) { +const char* TF_GraphDebugString(TF_Graph* graph, size_t* len) { tensorflow::mutex_lock c(graph->mu); const auto& debug_str = graph->graph.ToGraphDefDebug().DebugString(); *len = debug_str.size(); @@ -112,55 +116,56 @@ TF_CAPI_EXPORT extern const char* TF_GraphDebugString(TF_Graph* graph, return ret; } -// TODO(hongm): Replace this will a real implementation. -static tensorflow::Status BuildDatasetTest(TF_Graph* dataset_graph, - Node** dataset_node) { - tensorflow::mutex_lock c(dataset_graph->mu); - Tensor const_t(tensorflow::DT_INT32, tensorflow::TensorShape({})); - const_t.flat<tensorflow::int32>()(0) = 1; - - Node* const_node; - TF_RETURN_IF_ERROR(NodeBuilder("Const", "Const") - .Attr("dtype", tensorflow::DT_INT32) - .Attr("value", const_t) - .Finalize(&dataset_graph->graph, &const_node)); - - std::vector<NodeBuilder::NodeOut> input_list; - input_list.push_back(NodeBuilder::NodeOut(const_node, 0)); - - return NodeBuilder("TensorDataset", "TensorDataset") - .Input(input_list) - .Attr("Toutput_types", {tensorflow::DT_INT32}) - .Attr("output_shapes", {tensorflow::TensorShapeProto()}) - .Finalize(&dataset_graph->graph, dataset_node); -} - -// On success, returns a newly created TF_Function instance from -// `text_proto`. It must be deleted by calling TF_DeleteFunction. -static TF_Function* CreateFunctionFromTextProto(const char* text_proto, - TF_Status* status) { - tensorflow::FunctionDef fdef; - if (!tensorflow::protobuf::TextFormat::ParseFromString(text_proto, &fdef)) { +// On success, returns a set of TF_Function instances from `text_proto` of +// GraphDef type. These functions must be deleted by calling TF_DeleteFunction. +// +// If `mutate_proto_func` is non-NULL, run it over each FunctionDef proto, +// before creating a TF_Function out of the possibly mutated proto. +static std::vector<UniqueFuncPtr> CreateFunctionsFromTextProto( + const char* text_proto, + std::function<void(FunctionDef*)>* mutate_proto_func, TF_Status* status) { + tensorflow::GraphDef gdef; + if (!tensorflow::protobuf::TextFormat::ParseFromString(text_proto, &gdef)) { status->status = tensorflow::errors::Internal( - "Invalid text proto for FunctionDef: ", text_proto); - return nullptr; + "Invalid text proto for GraphDef: ", text_proto); + return {}; + } + const auto& fdef_lib = gdef.library(); + if (fdef_lib.gradient_size() > 0) { + status->status = tensorflow::errors::Internal( + "GradientDef is not supported in reading Dataset related functions: ", + text_proto); + return {}; + } + std::vector<UniqueFuncPtr> ret; + for (const auto& fdef : fdef_lib.function()) { + // Make a copy so that we can mutate it. + FunctionDef fdef_to_load = fdef; + if (mutate_proto_func) { + (*mutate_proto_func)(&fdef_to_load); + } + VLOG(1) << "Adding func to graph: " << fdef_to_load.DebugString(); + std::vector<char> binary_proto_buf(fdef_to_load.ByteSizeLong()); + fdef_to_load.SerializeToArray(binary_proto_buf.data(), + binary_proto_buf.size()); + auto func = TF_FunctionImportFunctionDef(binary_proto_buf.data(), + binary_proto_buf.size(), status); + if (!status->status.ok()) return {}; + ret.push_back(UniqueFuncPtr(func, TF_DeleteFunction)); } - std::vector<char> binary_proto_buf(fdef.ByteSizeLong()); - fdef.SerializeToArray(binary_proto_buf.data(), binary_proto_buf.size()); - return TF_FunctionImportFunctionDef(binary_proto_buf.data(), - binary_proto_buf.size(), status); + return ret; } -// On success, returns a newly created TF_Function instance from `proto_file`, -// and sets `dataset_name` to the created dataset name. The returned function -// must be deleted by calling TF_DeleteFunction. -// -// TODO(hongm): Support reading the file given by `proto_file`. -static TF_Function* LoadDatasetFunction(const char* proto_file, - std::string* dataset_name, - TF_Status* status) { +// On success, returns a newly created TF_Function instance encoding a dataset +// node stack that returns a sequence of 3 floats, and sets `dataset_name` to +// the created dataset name. The returned function must be deleted by calling +// TF_DeleteFunction. +static UniqueFuncPtr CreateFakeDatasetFunction(std::string* dataset_name, + TF_Status* status) { const char* func_def = R"PREFIX( -signature { +library { + function { + signature { name: "_make_dataset_d8de2712" output_arg { name: "TensorSliceDataset" @@ -217,53 +222,6917 @@ signature { ret { key: "TensorSliceDataset" value: "TensorSliceDataset:handle:0" - })PREFIX"; + } + } +} +)PREFIX"; *dataset_name = "_make_dataset_d8de2712"; - return CreateFunctionFromTextProto(func_def, status); + auto functions = CreateFunctionsFromTextProto( + func_def, /*mutate_proto_func*/ nullptr, status); + DCHECK_EQ(functions.size(), 1); + return std::move(functions[0]); } -// TODO(hongm): Use `file_path` in the implementation. -TF_Operation* TF_MakeIteratorGetNextWithDatasets(TF_Graph* graph, - const char* file_path, - TF_Function** dataset_func, - TF_Status* status) { - tensorflow::Status s; - - // We can parameterize the function name, if we ever need more than 1 - // iterators in a graph. - const std::string dataset_name = "UNIQUE_DATASET"; - - std::unique_ptr<TF_Graph, decltype(&TF_DeleteGraph)> dataset_graph( - TF_NewGraph(), TF_DeleteGraph); - Node* dataset_node = nullptr; - s = BuildDatasetTest(dataset_graph.get(), &dataset_node); - if (!s.ok()) { - status->status = s; - return nullptr; +// On success, returns a set of TF_Function instances encoding a dataset +// node stack that reads a Imagenet TFRecordFile dataset from `file_path`, and +// sets `dataset_name` to the created dataset name. The returned functions must +// be deleted by calling TF_DeleteFunction. +static std::vector<UniqueFuncPtr> CreateImagenetDatasetFunctions( + const char* file_path, std::string* dataset_name, TF_Status* status) { + const char* func_def = R"PREFIX( +library { + function { + signature { + name: "tf_map_func_91295dea" + input_arg { + name: "arg0" + type: DT_STRING + } + output_arg { + name: "FlatMapDataset" + type: DT_VARIANT + } + description: "A wrapper for Defun that facilitates shape inference." + is_stateful: true + } + node_def { + name: "flat_filenames/shape" + op: "Const" + attr { + key: "dtype" + value { + type: DT_INT32 + } + } + attr { + key: "value" + value { + tensor { + dtype: DT_INT32 + tensor_shape { + dim { + size: 1 + } + } + int_val: -1 + } + } + } + } + node_def { + name: "flat_filenames" + op: "Reshape" + input: "arg0" + input: "flat_filenames/shape:output:0" + attr { + key: "T" + value { + type: DT_STRING + } + } + attr { + key: "Tshape" + value { + type: DT_INT32 + } + } + } + node_def { + name: "TensorSliceDataset" + op: "TensorSliceDataset" + input: "flat_filenames:output:0" + attr { + key: "Toutput_types" + value { + list { + type: DT_STRING + } + } + } + attr { + key: "output_shapes" + value { + list { + shape { + } + } + } + } + } + node_def { + name: "FlatMapDataset" + op: "FlatMapDataset" + input: "TensorSliceDataset:handle:0" + attr { + key: "Targuments" + value { + list { + } + } + } + attr { + key: "f" + value { + func { + name: "tf_map_func_0cc8c35b" + } + } + } + attr { + key: "output_shapes" + value { + list { + shape { + } + } + } + } + attr { + key: "output_types" + value { + list { + type: DT_STRING + } + } + } + } + ret { + key: "FlatMapDataset" + value: "FlatMapDataset:handle:0" + } } - - TF_Output output{ToTF_Operation(dataset_node), 0}; - std::unique_ptr<TF_Function, decltype(&TF_DeleteFunction)> result_func( - TF_GraphToFunction(dataset_graph.get(), dataset_name.c_str(), - /*append_hash_to_fn_name*/ false, - /*num_opers*/ -1, - /*opers*/ nullptr, - /*numinputs*/ 0, - /*inputs*/ nullptr, - /*noutputs*/ 1, - /*outputs*/ &output, - /*outputnames*/ nullptr, - /*functionoptions*/ nullptr, "", status), - TF_DeleteFunction); - if (!status->status.ok()) { - return nullptr; + function { + signature { + name: "tf_map_func_0cc8c35b" + input_arg { + name: "arg0" + type: DT_STRING + } + output_arg { + name: "TFRecordDataset" + type: DT_VARIANT + } + description: "A wrapper for Defun that facilitates shape inference." + is_stateful: true + } + node_def { + name: "compression_type" + op: "Const" + attr { + key: "dtype" + value { + type: DT_STRING + } + } + attr { + key: "value" + value { + tensor { + dtype: DT_STRING + tensor_shape { + } + string_val: "" + } + } + } + } + node_def { + name: "buffer_size" + op: "Const" + attr { + key: "dtype" + value { + type: DT_INT64 + } + } + attr { + key: "value" + value { + tensor { + dtype: DT_INT64 + tensor_shape { + } + int64_val: 8388608 + } + } + } + } + node_def { + name: "TFRecordDataset" + op: "TFRecordDataset" + input: "arg0" + input: "compression_type:output:0" + input: "buffer_size:output:0" + } + ret { + key: "TFRecordDataset" + value: "TFRecordDataset:handle:0" + } + } + function { + signature { + name: "tf_map_func_74b6b15c" + input_arg { + name: "arg0" + type: DT_STRING + } + output_arg { + name: "Reshape_1" + type: DT_FLOAT + } + output_arg { + name: "sub_1" + type: DT_INT32 + } + description: "A wrapper for Defun that facilitates shape inference." + is_stateful: true + } + node_def { + name: "ParseSingleExample/key_image/class/label" + op: "Const" + attr { + key: "dtype" + value { + type: DT_INT64 + } + } + attr { + key: "value" + value { + tensor { + dtype: DT_INT64 + tensor_shape { + } + int64_val: -1 + } + } + } + } + node_def { + name: "ParseSingleExample/Reshape/shape" + op: "Const" + attr { + key: "dtype" + value { + type: DT_INT32 + } + } + attr { + key: "value" + value { + tensor { + dtype: DT_INT32 + tensor_shape { + dim { + } + } + } + } + } + } + node_def { + name: "ParseSingleExample/Reshape" + op: "Reshape" + input: "ParseSingleExample/key_image/class/label:output:0" + input: "ParseSingleExample/Reshape/shape:output:0" + attr { + key: "T" + value { + type: DT_INT64 + } + } + attr { + key: "Tshape" + value { + type: DT_INT32 + } + } + } + node_def { + name: "ParseSingleExample/key_image/class/text" + op: "Const" + attr { + key: "dtype" + value { + type: DT_STRING + } + } + attr { + key: "value" + value { + tensor { + dtype: DT_STRING + tensor_shape { + } + string_val: "" + } + } + } + } + node_def { + name: "ParseSingleExample/Reshape_1/shape" + op: "Const" + attr { + key: "dtype" + value { + type: DT_INT32 + } + } + attr { + key: "value" + value { + tensor { + dtype: DT_INT32 + tensor_shape { + dim { + } + } + } + } + } + } + node_def { + name: "ParseSingleExample/Reshape_1" + op: "Reshape" + input: "ParseSingleExample/key_image/class/text:output:0" + input: "ParseSingleExample/Reshape_1/shape:output:0" + attr { + key: "T" + value { + type: DT_STRING + } + } + attr { + key: "Tshape" + value { + type: DT_INT32 + } + } + } + node_def { + name: "ParseSingleExample/key_image/encoded" + op: "Const" + attr { + key: "dtype" + value { + type: DT_STRING + } + } + attr { + key: "value" + value { + tensor { + dtype: DT_STRING + tensor_shape { + } + string_val: "" + } + } + } + } + node_def { + name: "ParseSingleExample/Reshape_2/shape" + op: "Const" + attr { + key: "dtype" + value { + type: DT_INT32 + } + } + attr { + key: "value" + value { + tensor { + dtype: DT_INT32 + tensor_shape { + dim { + } + } + } + } + } + } + node_def { + name: "ParseSingleExample/Reshape_2" + op: "Reshape" + input: "ParseSingleExample/key_image/encoded:output:0" + input: "ParseSingleExample/Reshape_2/shape:output:0" + attr { + key: "T" + value { + type: DT_STRING + } + } + attr { + key: "Tshape" + value { + type: DT_INT32 + } + } + } + node_def { + name: "ParseSingleExample/key_image/format" + op: "Const" + attr { + key: "dtype" + value { + type: DT_STRING + } + } + attr { + key: "value" + value { + tensor { + dtype: DT_STRING + tensor_shape { + } + string_val: "jpeg" + } + } + } + } + node_def { + name: "ParseSingleExample/Reshape_3/shape" + op: "Const" + attr { + key: "dtype" + value { + type: DT_INT32 + } + } + attr { + key: "value" + value { + tensor { + dtype: DT_INT32 + tensor_shape { + dim { + } + } + } + } + } + } + node_def { + name: "ParseSingleExample/Reshape_3" + op: "Reshape" + input: "ParseSingleExample/key_image/format:output:0" + input: "ParseSingleExample/Reshape_3/shape:output:0" + attr { + key: "T" + value { + type: DT_STRING + } + } + attr { + key: "Tshape" + value { + type: DT_INT32 + } + } + } + node_def { + name: "ParseSingleExample/ParseSingleExample" + op: "ParseSingleExample" + input: "arg0" + input: "ParseSingleExample/Reshape:output:0" + input: "ParseSingleExample/Reshape_1:output:0" + input: "ParseSingleExample/Reshape_2:output:0" + input: "ParseSingleExample/Reshape_3:output:0" + attr { + key: "Tdense" + value { + list { + type: DT_INT64 + type: DT_STRING + type: DT_STRING + type: DT_STRING + } + } + } + attr { + key: "dense_keys" + value { + list { + s: "image/class/label" + s: "image/class/text" + s: "image/encoded" + s: "image/format" + } + } + } + attr { + key: "dense_shapes" + value { + list { + shape { + } + shape { + } + shape { + } + shape { + } + } + } + } + attr { + key: "num_sparse" + value { + i: 5 + } + } + attr { + key: "sparse_keys" + value { + list { + s: "image/object/bbox/xmax" + s: "image/object/bbox/xmin" + s: "image/object/bbox/ymax" + s: "image/object/bbox/ymin" + s: "image/object/class/label" + } + } + } + attr { + key: "sparse_types" + value { + list { + type: DT_FLOAT + type: DT_FLOAT + type: DT_FLOAT + type: DT_FLOAT + type: DT_INT64 + } + } + } + } + node_def { + name: "Reshape/shape" + op: "Const" + attr { + key: "dtype" + value { + type: DT_INT32 + } + } + attr { + key: "value" + value { + tensor { + dtype: DT_INT32 + tensor_shape { + dim { + } + } + } + } + } + } + node_def { + name: "Reshape" + op: "Reshape" + input: "ParseSingleExample/ParseSingleExample:dense_values:2" + input: "Reshape/shape:output:0" + attr { + key: "T" + value { + type: DT_STRING + } + } + attr { + key: "Tshape" + value { + type: DT_INT32 + } + } + } + node_def { + name: "decode_image/Substr/pos" + op: "Const" + attr { + key: "dtype" + value { + type: DT_INT32 + } + } + attr { + key: "value" + value { + tensor { + dtype: DT_INT32 + tensor_shape { + } + int_val: 0 + } + } + } + } + node_def { + name: "decode_image/Substr/len" + op: "Const" + attr { + key: "dtype" + value { + type: DT_INT32 + } + } + attr { + key: "value" + value { + tensor { + dtype: DT_INT32 + tensor_shape { + } + int_val: 3 + } + } + } + } + node_def { + name: "decode_image/Substr" + op: "Substr" + input: "Reshape:output:0" + input: "decode_image/Substr/pos:output:0" + input: "decode_image/Substr/len:output:0" + attr { + key: "T" 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2 + } + } + } + } + node_def { + name: "ParallelInterleaveDataset/prefetch_input_elements" + op: "Const" + attr { + key: "dtype" + value { + type: DT_INT64 + } + } + attr { + key: "value" + value { + tensor { + dtype: DT_INT64 + tensor_shape { + } + int64_val: 16 + } + } + } + } + node_def { + name: "ParallelInterleaveDataset" + op: "ParallelInterleaveDataset" + input: "RepeatDataset:handle:0" + input: "ParallelInterleaveDataset/cycle_length:output:0" + input: "ParallelInterleaveDataset/block_length:output:0" + input: "ParallelInterleaveDataset/sloppy:output:0" + input: "ParallelInterleaveDataset/buffer_output_elements:output:0" + input: "ParallelInterleaveDataset/prefetch_input_elements:output:0" + attr { + key: "Targuments" + value { + list { + } + } + } + attr { + key: "f" + value { + func { + name: "tf_map_func_91295dea" + } + } + } + attr { + key: "output_shapes" + value { + list { + shape { + } + } + } + } + attr { + key: "output_types" + value { + list { + type: DT_STRING + } + } + } + } + node_def { + name: "ShuffleDataset_2/buffer_size_1" + op: "Const" + attr { + key: "dtype" + value { + type: DT_INT64 + } + } + attr { + key: "value" + value { + tensor { + dtype: DT_INT64 + tensor_shape { + } + int64_val: 1024 + } + } + } + } + node_def { + name: "ShuffleDataset_2/seed_2" + op: "Const" + attr { + key: "dtype" + value { + type: DT_INT64 + } + } + attr { + key: "value" + value { + tensor { + dtype: DT_INT64 + tensor_shape { + } + int64_val: 0 + } + } + } + } + node_def { + name: "ShuffleDataset_2/seed2_2" + op: "Const" + attr { + key: "dtype" + value { + type: DT_INT64 + } + } + attr { + key: "value" + value { + tensor { + dtype: DT_INT64 + tensor_shape { + } + int64_val: 0 + } + } + } + } + node_def { + name: "ShuffleDataset_2" + op: "ShuffleDataset" + input: "ParallelInterleaveDataset:handle:0" + input: "ShuffleDataset_2/buffer_size_1:output:0" + input: "ShuffleDataset_2/seed_2:output:0" + input: "ShuffleDataset_2/seed2_2:output:0" + attr { + key: "output_shapes" + value { + list { + shape { + } + } + } + } + attr { + key: "output_types" + value { + list { + type: DT_STRING + } + } + } + attr { + key: "reshuffle_each_iteration" + value { + b: true + } + } + } + node_def { + name: "ParallelMapDataset/num_parallel_calls" + op: "Const" + attr { + key: "dtype" + value { + type: DT_INT32 + } + } + attr { + key: "value" + value { + tensor { + dtype: DT_INT32 + tensor_shape { + } + int_val: 64 + } + } + } + } + node_def { + name: "ParallelMapDataset" + op: "ParallelMapDataset" + input: "ShuffleDataset_2:handle:0" + input: "ParallelMapDataset/num_parallel_calls:output:0" + attr { + key: "Targuments" + value { + list { + } + } + } + attr { + key: "f" + value { + func { + name: "tf_map_func_74b6b15c" + } + } + } + attr { + key: "output_shapes" + value { + list { + shape { + dim { + size: 224 + } + dim { + size: 224 + } + dim { + size: 3 + } + } + shape { + } + } + } + } + attr { + key: "output_types" + value { + list { + type: DT_FLOAT + type: DT_INT32 + } + } + } + } + node_def { + name: "PrefetchDataset/buffer_size_2" + op: "Const" + attr { + key: "dtype" + value { + type: DT_INT64 + } + } + attr { + key: "value" + value { + tensor { + dtype: DT_INT64 + tensor_shape { + } + int64_val: 64 + } + } + } + } + node_def { + name: "PrefetchDataset" + op: "PrefetchDataset" + input: "ParallelMapDataset:handle:0" + input: "PrefetchDataset/buffer_size_2:output:0" + attr { + key: "output_shapes" + value { + list { + shape { + dim { + size: 224 + } + dim { + size: 224 + } + dim { + size: 3 + } + } + shape { + } + } + } + } + attr { + key: "output_types" + value { + list { + type: DT_FLOAT + type: DT_INT32 + } + } + } + } + node_def { + name: "BatchDataset/batch_size" + op: "Const" + attr { + key: "dtype" + value { + type: DT_INT64 + } + } + attr { + key: "value" + value { + tensor { + dtype: DT_INT64 + tensor_shape { + } + int64_val: 64 + } + } + } + } + node_def { + name: "BatchDataset" + op: "BatchDataset" + input: "PrefetchDataset:handle:0" + input: "BatchDataset/batch_size:output:0" + attr { + key: "output_shapes" + value { + list { + shape { + dim { + size: -1 + } + dim { + size: 224 + } + dim { + size: 224 + } + dim { + size: 3 + } + } + shape { + dim { + size: -1 + } + } + } + } + } + attr { + key: "output_types" + value { + list { + type: DT_FLOAT + type: DT_INT32 + } + } + } + } + node_def { + name: "FilterDataset/batch_size_1" + op: "Const" + attr { + key: "dtype" + value { + type: DT_INT64 + } + } + attr { + key: "value" + value { + tensor { + dtype: DT_INT64 + tensor_shape { + } + int64_val: 64 + } + } + } + } + node_def { + name: "FilterDataset" + op: "FilterDataset" + input: "BatchDataset:handle:0" + input: "FilterDataset/batch_size_1:output:0" + attr { + key: "Targuments" + value { + list { + type: DT_INT64 + } + } + } + attr { + key: "output_shapes" + value { + list { + shape { + dim { + size: -1 + } + dim { + size: 224 + } + dim { + size: 224 + } + dim { + size: 3 + } + } + shape { + dim { + size: -1 + } + } + } + } + } + attr { + key: "output_types" + value { + list { + type: DT_FLOAT + type: DT_INT32 + } + } + } + attr { + key: "predicate" + value { + func { + name: "tf_predicate_7089b845" + } + } + } + } + node_def { + name: "PrefetchDataset_1/buffer_size_3" + op: "Const" + attr { + key: "dtype" + value { + type: DT_INT64 + } + } + attr { + key: "value" + value { + tensor { + dtype: DT_INT64 + tensor_shape { + } + int64_val: 2 + } + } + } + } + node_def { + name: "PrefetchDataset_1" + op: "PrefetchDataset" + input: "FilterDataset:handle:0" + input: "PrefetchDataset_1/buffer_size_3:output:0" + attr { + key: "output_shapes" + value { + list { + shape { + dim { + size: 64 + } + dim { + size: 224 + } + dim { + size: 224 + } + dim { + size: 3 + } + } + shape { + dim { + size: 64 + } + } + } + } + } + attr { + key: "output_types" + value { + list { + type: DT_FLOAT + type: DT_INT32 + } + } + } + } + ret { + key: "PrefetchDataset_1" + value: "PrefetchDataset_1:handle:0" + } } +} +)PREFIX"; - TF_GraphCopyFunction(graph, result_func.get(), /*gradient*/ nullptr, status); + *dataset_name = "_make_dataset_5fa5e1f4"; + std::function<void(FunctionDef*)> mutate_proto_func = + [dataset_name, file_path](FunctionDef* fdef) { + VLOG(1) << "Processsing function " << fdef->DebugString(); + if (std::string(fdef->signature().name()) != *dataset_name) return; + // Change the input file pattern to `file_path`. + bool found = false; + for (auto& node_def : *fdef->mutable_node_def()) { + if (node_def.name() != "TensorSliceDataset/MatchingFiles/pattern" && + node_def.name() != "ShuffleDataset/MatchingFiles/pattern") + continue; + DCHECK_EQ(node_def.op(), "Const"); + DCHECK_GT(node_def.attr().count("value"), 0); + found = true; + DCHECK_EQ(node_def.attr().at("value").tensor().string_val(0), + "$(DATA_DIR)"); + VLOG(1) << "Setting the value of node_def " + "TensorSliceDataset/MatchingFiles/pattern to " + << file_path; + auto* tensor = (*node_def.mutable_attr())["value"].mutable_tensor(); + tensor->clear_string_val(); + tensor->add_string_val(file_path); + } + VLOG(1) << "Rewrote function to " << fdef->DebugString(); + DCHECK(found); + }; + return CreateFunctionsFromTextProto(func_def, &mutate_proto_func, status); +} - if (!status->status.ok()) { - return nullptr; +// Adds the input functions to `graph`. On success, returns the created +// IteratorGetNext node. +static TF_Operation* AddDatasetFunctionAndIteratorNodesToGraph( + const std::vector<UniqueFuncPtr>& funcs, const std::string& dataset_name, + const std::vector<tensorflow::DataType>& output_types, + const std::vector<tensorflow::TensorShapeProto>& output_shapes, + TF_Graph* graph, TF_Status* status) { + DCHECK(!dataset_name.empty()); + for (auto& func : funcs) { + TF_GraphCopyFunction(graph, func.get(), /*gradient*/ nullptr, status); + if (!status->status.ok()) { + return nullptr; + } } tensorflow::mutex_lock c(graph->mu); @@ -272,16 +7141,14 @@ TF_Operation* TF_MakeIteratorGetNextWithDatasets(TF_Graph* graph, func.set_name(dataset_name); // Run the iterator node on CPU. Node* oneshot_iterator_node; - std::vector<tensorflow::TensorShapeProto> output_shape_list; - output_shape_list.push_back(tensorflow::TensorShapeProto()); - s = NodeBuilder("OneShotIterator", "OneShotIterator") - .Device("/device:CPU:0") - .Attr("container", "") - .Attr("dataset_factory", func) - .Attr("output_types", {tensorflow::DT_INT32}) - .Attr("output_shapes", output_shape_list) - .Attr("shared_name", "") - .Finalize(&graph->graph, &oneshot_iterator_node); + tensorflow::Status s = NodeBuilder("OneShotIterator", "OneShotIterator") + .Device("/device:CPU:0") + .Attr("container", "") + .Attr("dataset_factory", func) + .Attr("output_types", output_types) + .Attr("output_shapes", output_shapes) + .Attr("shared_name", "") + .Finalize(&graph->graph, &oneshot_iterator_node); if (!s.ok()) { status->status = s; return nullptr; @@ -299,8 +7166,8 @@ TF_Operation* TF_MakeIteratorGetNextWithDatasets(TF_Graph* graph, s = NodeBuilder("IteratorGetNext", "IteratorGetNext") .Input(oneshot_iterator_node) .Device("/device:CPU:0") - .Attr("output_types", {tensorflow::DT_INT32}) - .Attr("output_shapes", output_shape_list) + .Attr("output_types", output_types) + .Attr("output_shapes", output_shapes) .Finalize(&graph->graph, &getnext_node); if (!s.ok()) { status->status = s; @@ -315,14 +7182,69 @@ TF_Operation* TF_MakeIteratorGetNextWithDatasets(TF_Graph* graph, } VLOG(1) << "Output graph: " << graph->graph.ToGraphDefDebug().DebugString(); - *dataset_func = result_func.release(); return ToTF_Operation(getnext_node); } -void TF_GetAttrScalarTensorShapeProto(TF_Buffer* value, TF_Status* status) { - status->status = Status::OK(); - auto shape = tensorflow::TensorShape({}); - tensorflow::TensorShapeProto shape_proto; - shape.AsProto(&shape_proto); - status->status = MessageToBuffer(shape_proto, value); +TF_Operation* TF_MakeFakeIteratorGetNextWithDatasets(TF_Graph* graph, + TF_Status* status) { + tensorflow::Status s; + + std::string dataset_name; + UniqueFuncPtr result_func = CreateFakeDatasetFunction(&dataset_name, status); + if (!status->status.ok()) { + return nullptr; + } + + std::vector<UniqueFuncPtr> funcs; + funcs.push_back(std::move(result_func)); + std::vector<tensorflow::TensorShapeProto> output_shape_list; + output_shape_list.push_back(tensorflow::TensorShapeProto()); + auto* getnext_node = AddDatasetFunctionAndIteratorNodesToGraph( + funcs, dataset_name, {tensorflow::DT_FLOAT}, output_shape_list, graph, + status); + if (!status->status.ok()) { + return nullptr; + } + + return getnext_node; +} + +TF_Operation* TF_MakeImagenetIteratorGetNextWithDatasets(TF_Graph* graph, + const char* file_path, + int batch_size, + TF_Status* status) { + tensorflow::Status s; + + std::string dataset_name; + const auto& funcs = + CreateImagenetDatasetFunctions(file_path, &dataset_name, status); + if (!status->status.ok()) { + return nullptr; + } + + std::vector<tensorflow::TensorShapeProto> output_shape_list; + // batch_size X 224 X 224 X 3 + auto image_shape = tensorflow::TensorShapeProto(); + image_shape.add_dim()->set_size(batch_size); + image_shape.add_dim()->set_size(224); + image_shape.add_dim()->set_size(224); + image_shape.add_dim()->set_size(3); + output_shape_list.push_back(image_shape); + + // batch_size + auto label_shape = tensorflow::TensorShapeProto(); + label_shape.add_dim()->set_size(batch_size); + output_shape_list.push_back(label_shape); + auto* getnext_node = AddDatasetFunctionAndIteratorNodesToGraph( + funcs, dataset_name, {tensorflow::DT_FLOAT, tensorflow::DT_INT32}, + output_shape_list, graph, status); + if (!status->status.ok()) { + return nullptr; + } + + tensorflow::mutex_lock c(graph->mu); + VLOG(1) << "The extended graph: " + << graph->graph.ToGraphDefDebug().DebugString(); + + return getnext_node; } |