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modified tensorflow parser from graph branch #522
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1 @@ | ||
| protoc -I=.. --cpp_out=.. ../tensorflow/core/framework/*.proto |
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,40 @@ | ||
| #include <iostream> | ||
| #include <fstream> | ||
| #include <sstream> | ||
| #include <string> | ||
| #include <map> | ||
| #include "tiny_dnn/io/tensorflow/proto_parser.h" | ||
| using namespace std; | ||
| using namespace tiny_cnn; | ||
| using namespace tensorflow; | ||
|
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| // Main function: Reads the graph definition from a file and prints all | ||
| // the information inside. | ||
| int main(int argc, char* argv[]) { | ||
| // Verify that the version of the library that we linked against is | ||
| // compatible with the version of the headers we compiled against. | ||
| GOOGLE_PROTOBUF_VERIFY_VERSION; | ||
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| if (argc != 2) { | ||
| cerr << "Usage: " << argv[0] << " GRAPH_DEF_FILE" << endl; | ||
| return -1; | ||
| } | ||
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| tensorflow::GraphDef graph_def; | ||
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| { | ||
| // Read the existing graph. | ||
| fstream input(argv[1], ios::in | ios::binary); | ||
| if (!graph_def.ParseFromIstream(&input)) { | ||
| cerr << "Failed to parse graph." << endl; | ||
| return -1; | ||
| } | ||
| } | ||
|
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| list_nodes(graph_def); | ||
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| // Optional: Delete all global objects allocated by libprotobuf. | ||
| google::protobuf::ShutdownProtobufLibrary(); | ||
|
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||
| return 0; | ||
| } |
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,27 @@ | ||
| syntax = "proto3"; | ||
|
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| package tensorflow; | ||
| option cc_enable_arenas = true; | ||
| option java_outer_classname = "AllocationDescriptionProtos"; | ||
| option java_multiple_files = true; | ||
| option java_package = "org.tensorflow.framework"; | ||
|
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| message AllocationDescription { | ||
| // Total number of bytes requested | ||
| int64 requested_bytes = 1; | ||
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| // Total number of bytes allocated if known | ||
| int64 allocated_bytes = 2; | ||
|
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| // Name of the allocator used | ||
| string allocator_name = 3; | ||
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| // Identifier of the allocated buffer if known | ||
| int64 allocation_id = 4; | ||
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| // Set if this tensor only has one remaining reference | ||
| bool has_single_reference = 5; | ||
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| // Address of the allocation. | ||
| uint64 ptr = 6; | ||
| }; | ||
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,60 @@ | ||
| syntax = "proto3"; | ||
|
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| package tensorflow; | ||
| option cc_enable_arenas = true; | ||
| option java_outer_classname = "AttrValueProtos"; | ||
| option java_multiple_files = true; | ||
| option java_package = "org.tensorflow.framework"; | ||
|
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| import "tensorflow/core/framework/tensor.proto"; | ||
| import "tensorflow/core/framework/tensor_shape.proto"; | ||
| import "tensorflow/core/framework/types.proto"; | ||
|
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| // Protocol buffer representing the value for an attr used to configure an Op. | ||
| // Comment indicates the corresponding attr type. Only the field matching the | ||
| // attr type may be filled. | ||
| message AttrValue { | ||
| message ListValue { | ||
| repeated bytes s = 2; // "list(string)" | ||
| repeated int64 i = 3 [packed = true]; // "list(int)" | ||
| repeated float f = 4 [packed = true]; // "list(float)" | ||
| repeated bool b = 5 [packed = true]; // "list(bool)" | ||
| repeated DataType type = 6 [packed = true]; // "list(type)" | ||
| repeated TensorShapeProto shape = 7; // "list(shape)" | ||
| repeated TensorProto tensor = 8; // "list(tensor)" | ||
| // TODO(zhifengc/josh11b): implements list(func) if needed. | ||
| } | ||
|
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| oneof value { | ||
| bytes s = 2; // "string" | ||
| int64 i = 3; // "int" | ||
| float f = 4; // "float" | ||
| bool b = 5; // "bool" | ||
| DataType type = 6; // "type" | ||
| TensorShapeProto shape = 7; // "shape" | ||
| TensorProto tensor = 8; // "tensor" | ||
| ListValue list = 1; // any "list(...)" | ||
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| // "func" represents a function. func.name is a function's name or | ||
| // a primitive op's name. func.attr.first is the name of an attr | ||
| // defined for that function. func.attr.second is the value for | ||
| // that attr in the instantiation. | ||
| NameAttrList func = 10; | ||
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| // This is a placeholder only used in nodes defined inside a | ||
| // function. It indicates the attr value will be supplied when | ||
| // the function is instantiated. For example, let us suppose a | ||
| // node "N" in function "FN". "N" has an attr "A" with value | ||
| // placeholder = "foo". When FN is instantiated with attr "foo" | ||
| // set to "bar", the instantiated node N's attr A will have been | ||
| // given the value "bar". | ||
| string placeholder = 9; | ||
| } | ||
| } | ||
|
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| // A list of attr names and their values. The whole list is attached | ||
| // with a string name. E.g., MatMul[T=float]. | ||
| message NameAttrList { | ||
| string name = 1; | ||
| map<string, AttrValue> attr = 2; | ||
| } |
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,50 @@ | ||
| syntax = "proto3"; | ||
|
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| package tensorflow; | ||
| option cc_enable_arenas = true; | ||
| option java_outer_classname = "CostGraphProtos"; | ||
| option java_multiple_files = true; | ||
| option java_package = "org.tensorflow.framework"; | ||
|
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| message CostGraphDef { | ||
| message Node { | ||
| // The name of the node. | ||
| string name = 1; | ||
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| // The device of the node. | ||
| string device = 2; | ||
|
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| // The id of the node. | ||
| int32 id = 3; | ||
|
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| // Inputs of this node. They must be executed before this node can be | ||
| // executed. An input is a particular output of another node, specified | ||
| // by the node id and the output index. | ||
| message InputInfo { | ||
| int32 preceding_node = 1; | ||
| int32 preceding_port = 2; | ||
| } | ||
| repeated InputInfo input_info = 4; | ||
|
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| // Outputs of this node. | ||
| message OutputInfo { | ||
| int64 size = 1; | ||
| // If >= 0, the output is an alias of an input. Note that an alias input | ||
| // may itself be an alias. The algorithm will therefore need to follow | ||
| // those pointers. | ||
| int64 alias_input_port = 2; | ||
| } | ||
| repeated OutputInfo output_info = 5; | ||
|
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| // Temporary memory used by this node. | ||
| int64 temporary_memory_size = 6; | ||
|
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| // If true, the output is permanent: it can't be discarded, because this | ||
| // node is part of the "final output". Nodes may depend on final nodes. | ||
| bool is_final = 7; | ||
|
|
||
| // Ids of the control inputs for this node. | ||
| repeated int32 control_input = 8; | ||
| } | ||
| repeated Node node = 1; | ||
| } |
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,38 @@ | ||
| syntax = "proto3"; | ||
|
|
||
| package tensorflow; | ||
| option cc_enable_arenas = true; | ||
| option java_outer_classname = "DeviceAttributesProtos"; | ||
| option java_multiple_files = true; | ||
| option java_package = "org.tensorflow.framework"; | ||
|
|
||
| // BusAdjacency identifies the ability of a device to participate in | ||
| // maximally efficient DMA operations within the local context of a | ||
| // process. | ||
| // | ||
| // This is currently ignored. | ||
| enum BusAdjacency { | ||
| BUS_0 = 0; | ||
| BUS_1 = 1; | ||
| BUS_ANY = 2; | ||
| BUS_NUM_ADJACENCIES = 3; | ||
| }; | ||
|
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| message DeviceAttributes { | ||
| string name = 1; | ||
|
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| // String representation of device_type. | ||
| string device_type = 2; | ||
|
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| // Memory capacity of device in bytes. | ||
| int64 memory_limit = 4; | ||
|
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| BusAdjacency bus_adjacency = 5; | ||
|
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| // A device is assigned a global unique number each time it is | ||
| // initialized. "incarnation" should never be 0. | ||
| fixed64 incarnation = 6; | ||
|
|
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| // String representation of the physical device that this device maps to. | ||
| string physical_device_desc = 7; | ||
| } |
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,95 @@ | ||
| syntax = "proto3"; | ||
|
|
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| package tensorflow; | ||
| option cc_enable_arenas = true; | ||
| option java_outer_classname = "FunctionProtos"; | ||
| option java_multiple_files = true; | ||
| option java_package = "org.tensorflow.framework"; | ||
|
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| import "tensorflow/core/framework/attr_value.proto"; | ||
| import "tensorflow/core/framework/op_def.proto"; | ||
|
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| // A library is a set of named functions. | ||
| message FunctionDefLibrary { | ||
| repeated FunctionDef function = 1; | ||
| repeated GradientDef gradient = 2; | ||
| } | ||
|
|
||
| // A function can be instantiated when the runtime can bind every attr | ||
| // with a value. When a GraphDef has a call to a function, it must | ||
| // have binding for every attr defined in the signature. | ||
| // | ||
| // TODO(zhifengc): | ||
| // * device spec, etc. | ||
| message FunctionDef { | ||
| // The definition of the function's name, arguments, return values, | ||
| // attrs etc. | ||
| OpDef signature = 1; | ||
|
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| // The body of the function. | ||
| repeated Node node = 2; // function.node.ret[*] are unique. | ||
|
|
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| // A node is a multi-value assignment: | ||
| // (ret[0], ret[1], ...) = func(arg[0], arg[1], ...) | ||
| // | ||
| // By convention, "func" is resolved by consulting with a user-defined | ||
| // library first. If not resolved, "func" is assumed to be a builtin op. | ||
| message Node { | ||
| // This node produces multiple outputs. They are named ret[0], | ||
| // ret[1], ..., etc. | ||
| // | ||
| // REQUIRES: function.node.ret[*] are unique across all nodes. | ||
| // REQUIRES: ret.size == func/op def's number of output args. | ||
| repeated string ret = 1; | ||
|
|
||
| // The op/function name. | ||
| string op = 2; | ||
|
|
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| // Arguments passed to this func/op. | ||
| // | ||
| // arg[i] must be either one of | ||
| // function.signature.input_args[*].name or one of | ||
| // function.node[*].ret[*]. | ||
| // | ||
| // REQUIRES: arg.size == func/op def's number of input args. | ||
| repeated string arg = 3; | ||
|
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| // Control dependencies. | ||
| // | ||
| // dep[i] must be one of function.node[*].ret[*] or one of | ||
| // function.signature.input_args[*].name. | ||
| repeated string dep = 4; | ||
|
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| // Attrs. | ||
| // | ||
| // 'attr' maps names defined by 'func's attr defs to attr values. | ||
| // attr values may have placeholders which are substituted | ||
| // recursively by concrete values when this node is instantiated. | ||
| // These placeholders must name an attr listed in the FunctionDef's | ||
| // signature. | ||
| map<string, AttrValue> attr = 5; | ||
| } | ||
| } | ||
|
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||
| // GradientDef defines the gradient function of a function defined in | ||
| // a function library. | ||
| // | ||
| // A gradient function g (specified by gradient_func) for a function f | ||
| // (specified by function_name) must follow the following: | ||
| // | ||
| // The function 'f' must be a numerical function which takes N inputs | ||
| // and produces M outputs. Its gradient function 'g', which is a | ||
| // function taking N + M inputs and produces N outputs. | ||
| // | ||
| // I.e. if we have | ||
| // (y1, y2, ..., y_M) = f(x1, x2, ..., x_N), | ||
| // then, g is | ||
| // (dL/dx1, dL/dx2, ..., dL/dx_N) = g(x1, x2, ..., x_N, | ||
| // dL/dy1, dL/dy2, ..., dL/dy_M), | ||
| // where L is a scalar-value function of (x1, x2, ..., xN) (e.g., the | ||
| // loss function). dL/dx_i is the partial derivative of L with respect | ||
| // to x_i. | ||
| message GradientDef { | ||
| string function_name = 1; // The function name. | ||
| string gradient_func = 2; // The gradient function's name. | ||
| } |
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@wangyida this files should go to
tiny_dnn/io/tensorflow