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tensorflow/c/experimental/next_pluggable_device/c_api.cc
const tensorflow::Tensor& arg_tensor = cc_ctx->input(index); absl::Status cc_status; if (arg_tensor.dtype() != tensorflow::DT_RESOURCE) { cc_status = absl::InvalidArgumentError( absl::StrCat("Trying to obtain resource handle from Input[", index, "], which is not type DT_RESOURCE.")); status->status = cc_status; return nullptr; } const tensorflow::ResourceHandle& handle =
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Apr 22 05:48:24 UTC 2024 - 13.9K bytes - Viewed (0) -
tensorflow/compiler/mlir/tfr/passes/raise_to_tf.cc
} // Derive the output types. The result type is derived by using the // attributes attched to the result type of the signature. The attribute // value should be either in the attribute argument list or the derived // attribute from the input tensors. All the result type // are unranked, and shape inference should be applied afterwards. SmallVector<Type, 4> output_types;
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 21.8K 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/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) -
tensorflow/compiler/jit/shape_inference_test.cc
}; TF_EXPECT_OK(ShapeAnnotationsMatch(graph, shape_info, expected)); } TEST(ShapeInferenceTest, WhileLoopWithResource) { // Graph: // x = resource_variable_ops.var_handle_op(dtype=dtypes.float32, shape=[2, 3]) // y = control_flow_ops.while_loop(lambda _: true, lambda x: x, [x]) Graph graph(OpRegistry::Global()); { Scope scope = Scope::NewRootScope().ExitOnError(); auto x =
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri May 31 00:41:19 UTC 2024 - 10.3K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/schema/schema.fbs
// When set, quantized_bias_type defines the dtype for both bias and accumulator. quantized_bias_type: TensorType; } table ExpandDimsOptions { } table SparseToDenseOptions { validate_indices:bool; } table EqualOptions { } table NotEqualOptions { } table ShapeOptions { // Optional output type of the operation (int32 or int64). Defaults to int32.
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri May 03 18:01:23 UTC 2024 - 41.7K bytes - Viewed (0) -
tensorflow/compiler/mlir/tfrt/BUILD
), ) tf_cc_binary( name = "bef_executor", testonly = True, visibility = [":friends"], deps = [ "@tf_runtime//:dtype", "@tf_runtime//:simple_tracing_sink", "@tf_runtime//tools:bef_executor_expensive_kernels", "@tf_runtime//tools:bef_executor_lib", "@tf_runtime//tools:bef_executor_lightweight_kernels",
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue May 28 19:04:21 UTC 2024 - 23.6K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/transforms/tf_saved_model_freeze_variables.cc
ElementsAttr GetTensorValueAsElementsAttr( TF::VarHandleOp var_handle_op, const tensorflow::Tensor& resource_tensor, const tensorflow::DeviceMgr* mgr, OpBuilder builder) { if (resource_tensor.dtype() != tensorflow::DT_RESOURCE) { return GetTensorValueAsElementsAttr(resource_tensor, builder); } auto handle = resource_tensor.scalar<tensorflow::ResourceHandle>()();
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 09:56:53 UTC 2024 - 19.4K bytes - Viewed (0)