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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/c/c_api.cc
metadata.type = TF_ATTR_INT; } else if (typestr == "list(float)") { metadata.type = TF_ATTR_FLOAT; } else if (typestr == "list(bool)") { metadata.type = TF_ATTR_BOOL; } else if (typestr == "list(type)") { metadata.type = TF_ATTR_TYPE; } else if (typestr == "list(shape)") { metadata.type = TF_ATTR_SHAPE;
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Apr 15 03:35:10 UTC 2024 - 102.3K bytes - Viewed (0) -
tensorflow/c/eager/c_api_test_util.cc
TF_Status* status = TF_NewStatus(); // Create the variable handle. TFE_Op* op = TFE_NewOp(ctx, "VarHandleOp", status); if (TF_GetCode(status) != TF_OK) return nullptr; TFE_OpSetAttrType(op, "dtype", TF_FLOAT); TFE_OpSetAttrShape(op, "shape", {}, 0, status); TFE_OpSetAttrString(op, "container", "localhost", 0); TFE_OpSetAttrString(op, "shared_name", "", 0); if (!device_name.empty()) {
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Feb 21 22:37:46 UTC 2024 - 23.5K 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/python_api.cc
auto* out_shape_and_type = handle_data.add_shape_and_type(); ic->ShapeHandleToProto(p.shape, out_shape_and_type->mutable_shape()); out_shape_and_type->set_dtype(p.dtype); *out_shape_and_type->mutable_type() = p.type; } } string result; handle_data.SerializeToString(&result); return result; } void SetHandleShapeAndType(TF_Graph* graph, TF_Output output, const void* proto,
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Jul 12 18:48:56 UTC 2023 - 3.5K bytes - Viewed (0) -
tensorflow/cc/gradients/math_grad.cc
REGISTER_NO_GRADIENT_OP("Floor"); // Conjugate helper function returns the conjugate of an Output if it // is complex valued. Output ConjugateHelper(const Scope& scope, const Output& out) { DataType dtype = out.type(); if (dtype == DT_COMPLEX64 || dtype == DT_COMPLEX128) { return Conj(scope, out); } else { return out; } } // TODO(andydavis) Add control dependencies to gradient functions (as needed).
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri Aug 25 18:20:20 UTC 2023 - 50.7K bytes - Viewed (0) -
tensorflow/c/experimental/grappler/grappler_test.cc
tensorflow::OpInfo::TensorProperties in_props; Status s = tensorflow::BufferToMessage(in_props_buf[0], &in_props); TF_ASSERT_OK(s); EXPECT_EQ(DT_FLOAT, in_props.dtype()); EXPECT_FALSE(in_props.shape().unknown_rank()); EXPECT_EQ(2, in_props.shape().dim_size()); EXPECT_EQ(10, in_props.shape().dim(0).size()); EXPECT_EQ(1, in_props.shape().dim(1).size());
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 13 22:30:58 UTC 2023 - 11.6K bytes - Viewed (0) -
tensorflow/cc/framework/cc_op_gen_util.cc
} strings::StrAppend(&ret, "}"); return ret; } string PrintTensor(const TensorProto& tensor_proto) { Tensor t(tensor_proto.dtype()); CHECK(t.FromProto(tensor_proto)); const int64_t num_elts = t.NumElements(); switch (t.dtype()) { case DT_FLOAT: return PrintArray(num_elts, t.flat<float>().data()); case DT_DOUBLE: return PrintArray(num_elts, t.flat<double>().data());
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Feb 26 00:57:05 UTC 2024 - 25K 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/compiler/jit/xla_tensor.cc
} else { return se::DeviceMemoryBase(const_cast<char*>(tensor.tensor_data().data()), tensor.tensor_data().size()); } } Status XlaTensor::AllocateShapedBuffer(DataType dtype, const xla::Shape& on_device_shape, xla::LocalClient* client, int device_ordinal) { xla::Shape on_host_shape =
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Feb 22 08:47:20 UTC 2024 - 4.5K bytes - Viewed (0)