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Results 21 - 30 of 65 for num_inputs (0.18 sec)
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tensorflow/cc/gradients/nn_grad.cc
"FusedBatchNorm requires at least 5 outputs"); } if (grad_inputs.empty()) { return errors::InvalidArgument("FusedBatchNorm grad requires 1 grad input"); } if (op.num_inputs() < 3) { return errors::InvalidArgument("FusedBatchNorm has too few inputs"); } Output x = op.input(0); Output grad_y = grad_inputs[0]; Output scale = op.input(1); float epsilon;
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri May 27 23:34:33 UTC 2022 - 24.5K bytes - Viewed (0) -
tensorflow/cc/framework/ops.h
/// @addtogroup core /// @{ /// Represents a node in the computation graph. class Operation { public: Operation() : node_(nullptr) {} explicit Operation(Node* n); int32 num_inputs() const { return node_->num_inputs(); } DataType input_type(int32_t o) const { return node_->input_type(o); } Output input(int32_t i) const; int32 num_outputs() const { return node_->num_outputs(); }
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Sat Apr 13 05:57:22 UTC 2024 - 10.5K bytes - Viewed (0) -
tensorflow/cc/gradients/math_grad.cc
// hence dx_k = dy for all x_k // So the gradient for AddN just transfers the incoming gradient to // all outgoing gradients. auto incoming = Identity(scope, grad_inputs[0]); for (int32_t i = 0; i < op.num_inputs(); ++i) { grad_outputs->push_back(incoming); } return scope.status(); } REGISTER_GRADIENT_OP("AddN", AddNGrad); Status PowGrad(const Scope& scope, const Operation& op,
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/eager/parallel_device/parallel_device.cc
reinterpret_cast<NamedParallelDevice*>(device_info); std::vector<MaybeParallelTensorUnowned> typed_inputs; int num_inputs = TFE_OpGetFlatInputCount(original_op, status); if (TF_GetCode(status) != TF_OK) return; typed_inputs.reserve(num_inputs); for (int i = 0; i < num_inputs; ++i) { TFE_TensorHandle* input = TFE_OpGetFlatInput(original_op, i, status); if (TF_GetCode(status) != TF_OK) return;
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Mar 29 22:05:31 UTC 2023 - 18.3K bytes - Viewed (0) -
tensorflow/compiler/jit/xla_kernel_creator_test.cc
ASSERT_TRUE(status.ok()) << status.ToString(); EXPECT_EQ("XTimesY", kernel_->name()); EXPECT_EQ("XTimesY", kernel_->type_string()); EXPECT_EQ(2, kernel_->num_inputs()); EXPECT_EQ(DT_FLOAT, kernel_->input_type(0)); EXPECT_EQ(DT_RESOURCE, kernel_->input_type(1)); EXPECT_EQ(DEVICE_MEMORY, kernel_->input_memory_types()[0]); EXPECT_EQ(HOST_MEMORY, kernel_->input_memory_types()[1]);
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue May 16 01:39:55 UTC 2023 - 5.7K bytes - Viewed (0) -
tensorflow/c/kernels.cc
} #endif // defined(IS_MOBILE_PLATFORM) || defined(IS_SLIM_BUILD) } int TF_NumInputs(TF_OpKernelContext* ctx) { auto* cc_ctx = reinterpret_cast<::tensorflow::OpKernelContext*>(ctx); return cc_ctx->num_inputs(); } int TF_NumOutputs(TF_OpKernelContext* ctx) { auto* cc_ctx = reinterpret_cast<::tensorflow::OpKernelContext*>(ctx); return cc_ctx->num_outputs(); }
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue May 28 22:53:47 UTC 2024 - 36K bytes - Viewed (0) -
tensorflow/cc/gradients/data_flow_grad.cc
// grad = [[g_1, g_2], [g_3, g_4], [g_5, g_6]] // indices and data are two equal-sized lists passed // into DynamicStitch. // num_values = 2 int32_t num_values = op.num_inputs() / 2; // Stop propagation along the indices list for (int32_t i = 0; i < num_values; i++) { grad_outputs->push_back(NoGradient()); }
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Sat Jul 24 13:40:35 UTC 2021 - 5.8K bytes - Viewed (0) -
tensorflow/c/eager/c_api_unified_experimental.h
// returned through the provided TF_OutputList. // Any active tape will observe the effects of this execution. void TF_ExecuteOperation(TF_AbstractOp* op, int num_inputs, TF_AbstractTensor* const* inputs, TF_OutputList* o, TF_Status* s); // Creates a new TF_AbstractFunction from the current tracing states in the
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Sun Oct 24 11:27:00 UTC 2021 - 7K bytes - Viewed (0) -
tensorflow/c/kernels_test.cc
.Attr("SomeDataTypeAttr: type"); static int num_inputs = 0; static int num_outputs = 0; // A kernel whose Compute function has a side-effect of updating num_inputs // and num_outputs. Various functions on TF_OpKernelContext are also // exercised. auto my_compute_func = [](void* kernel, TF_OpKernelContext* ctx) { num_inputs = TF_NumInputs(ctx); num_outputs = TF_NumOutputs(ctx);
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Sep 06 19:12:29 UTC 2023 - 50.4K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/tensorflow/calibrator/calibration_statistics_saver_op.cc
absl::AbortedError( "The `ids` and `calibration_methods` must have the same size.")); // Check the number and type of inputs. OP_REQUIRES(context, context->num_inputs() == ids_.size() * 3, absl::AbortedError("The number of inputs must be three times " "the size of the `ids` list.")); for (int i = 0; i < ids_.size(); ++i) {
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon May 13 01:31:23 UTC 2024 - 8K bytes - Viewed (0)