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tensorflow/compiler/jit/compilability_check_util.h
op_name == "TruncatedNormal" || op_name == "Multinomial"; } bool OpProducesOrConsumesVariant(const Node& node) const { auto is_variant = [](DataType dtype) { return dtype == DT_VARIANT; }; return absl::c_any_of(node.input_types(), is_variant) || absl::c_any_of(node.output_types(), is_variant); } bool HasXLAKernel(const Node& node,
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Sep 06 19:12:29 UTC 2023 - 14.9K bytes - Viewed (0) -
tensorflow/c/experimental/saved_model/core/saved_model_utils.cc
tensorflow::TensorShape shape(variable.shape()); tensorflow::DataType dtype = variable.dtype(); std::vector<std::string> component_devices; for (const auto& component : variable.experimental_distributed_variable_components()) { component_devices.push_back(component.device()); } TF_RETURN_IF_ERROR(Variable::CreateUninitialized( ctx, dtype, shape, name,
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Jan 12 19:17:46 UTC 2023 - 24K bytes - Viewed (0) -
tensorflow/c/eager/immediate_execution_context.h
virtual AbstractTensorInterface* CreateBoolScalar(bool value) = 0; // Tensor creation functions virtual AbstractTensorInterface* CreateTensor( DataType dtype, absl::Span<const int64_t> dim_sizes) = 0; typedef void (*MemoryReleaser)(void* data, size_t len, void* arg); // Create a tensor instance from the given data buffer and description.
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Jul 06 08:34:00 UTC 2023 - 12.3K bytes - Viewed (0) -
tensorflow/c/eager/tape.h
// pushes and pops at the back. std::stack<AccumulatorCallState> call_state_; }; // Template instantiations here inline bool IsDtypeTrainable(DataType dtype) { switch (dtype) { case DT_HALF: case DT_BFLOAT16: case DT_FLOAT: case DT_DOUBLE: case DT_COMPLEX64: case DT_COMPLEX128: case DT_RESOURCE: case DT_VARIANT:
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Apr 02 12:40:29 UTC 2024 - 47.2K bytes - Viewed (0) -
tensorflow/c/eager/c_api_experimental.cc
} tensorflow::AbstractTensorInterface* t = tensorflow::unwrap(ctx)->CreateTensor( static_cast<tensorflow::DataType>(dtype), dimvec); if (t == nullptr) { status->status = tensorflow::errors::InvalidArgument("Unsupported dtype: ", dtype); return nullptr; } return new TF_Tensor{t}; } TFE_TensorHandle* TFE_NewTensorHandleFromTensor(TFE_Context* ctx, TF_Tensor* t,
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 11 23:52:39 UTC 2024 - 35.9K bytes - Viewed (0) -
tensorflow/compiler/jit/xla_device.cc
Status DefaultPaddedShapeFn(const Tensor& tensor, xla::Shape* shape) { const tensorflow::XlaTensor* xla_tensor = tensorflow::XlaTensor::FromTensor(&tensor); if (xla_tensor == nullptr) { return TensorShapeToXLAShape(tensor.dtype(), tensor.shape(), shape); } const xla::ShapedBuffer& shaped_buffer = xla_tensor->shaped_buffer(); *shape = shaped_buffer.on_device_shape(); return absl::OkStatus(); }
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon May 20 21:05:42 UTC 2024 - 24.3K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/python/tf_tfl_flatbuffer_helpers.cc
"'h_scale' type: 'float'} attr : { name: 'max_classes_per_detection' " "type: 'int'} attr : { name: 'max_detections' type: 'int'} attr : { " "name: 'nms_iou_threshold' type: 'float'} attr : { name: " "'nms_score_threshold' type: 'float'} attr : { name: 'num_classes' type: " "'int'} attr : { name: 'w_scale' type: 'float'} attr : { name: 'x_scale' "
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Sun May 12 12:39:37 UTC 2024 - 17.3K bytes - Viewed (0) -
tensorflow/compiler/jit/xla_launch_util_test.cc
CreateContext(); std::vector<XlaCompiler::Argument> args(2); args[0].kind = XlaCompiler::Argument::kParameter; args[0].type = DT_INT32; args[0].shape = TensorShape({1, 3}); args[1].kind = XlaCompiler::Argument::kParameter; args[1].type = DT_INT32; args[1].shape = TensorShape({1, 3}); const XlaCompiler::CompilationResult* result; xla::PjRtLoadedExecutable* executable;
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Feb 21 09:53:30 UTC 2024 - 28.8K bytes - Viewed (0) -
tensorflow/c/c_api_experimental.h
TF_Status* status); // Information about the shape of a Tensor and its type. struct TF_ShapeAndType { // Number of dimensions. -1 indicates unknown rank. int num_dims; // Array of dimensions. -1 indicates unknown dim. int64_t* dims; // The data type. May be 0 to denote unknown type. TF_DataType dtype; }; typedef struct TF_ShapeAndType TF_ShapeAndType;
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 27 21:07:00 UTC 2023 - 15.1K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/utils/tf_xla_mlir_translate.cc
<< compilation_result.xla_output_shape.ToString() << '\n'; for (const auto& xla_output_description : compilation_result.outputs) { output << "// XlaOutputDescription type=" << DataTypeString(xla_output_description.type) << " shape=(" << absl::StrJoin(xla_output_description.shape.dim_sizes(), ", ") << ')'; if (xla_output_description.input_index >= 0)
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 18.8K bytes - Viewed (0)