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Results 81 - 90 of 123 for input_dtype (0.18 sec)
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tensorflow/compiler/mlir/lite/tf_to_tfl_flatbuffer.cc
return GraphdefToSplattedMlirTranslateFunction( file->getBuffer(), input_arrays, input_dtypes, input_shapes, output_arrays, control_output_arrays, graphdef_conversion_options, context); } return GraphdefToMlirTranslateFunction(file->getBuffer(), input_arrays, input_dtypes, input_shapes, output_arrays, control_output_arrays,
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri May 03 18:01:23 UTC 2024 - 23.8K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/translate/tf_mlir_translate_cl.cc
// Import options. // NOLINTNEXTLINE opt<std::string> input_arrays( "tf-input-arrays", llvm::cl::desc("Input tensor names, separated by ','"), llvm::cl::init("")); // NOLINTNEXTLINE opt<std::string> input_dtypes( "tf-input-data-types", llvm::cl::desc("(Optional) Input tensor data types, separated by ','. Use " "'' if a single data type is skipped. The data type from "
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Aug 10 20:59:50 UTC 2023 - 5.5K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/transforms/optimize.cc
static bool AreInputDimensionsOneInAxes(Value input, const mlir::Attribute &axes) { RankedTensorType input_type = mlir::dyn_cast_or_null<RankedTensorType>(input.getType()); if (!input_type) return false; auto type_shape = input_type.getShape(); DenseIntElementsAttr axes_attr = mlir::dyn_cast_or_null<DenseIntElementsAttr>(axes); if (!axes_attr) return false;
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Apr 30 00:40:15 UTC 2024 - 102.3K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/quantization/ir/ConvertSimQuant.cc
auto qbarrier = rewriter.create<QuantizeCastOp>(op.getLoc(), quantizedType, op.getInputs()); rewriter.replaceOpWithNewOp<DequantizeCastOp>(op, converter.input_type, qbarrier.getResult()); return false; } }; class ConstFakeQuantRewrite : public FakeQuantRewrite<ConstFakeQuantRewrite, ConstFakeQuant> {
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed May 08 02:10:16 UTC 2024 - 6K bytes - Viewed (0) -
tensorflow/compiler/jit/xla_cluster_util.cc
if (!s.ok()) { return std::nullopt; } return attr_value->s(); } bool HasResourceInputOrOutput(const Node& node) { return std::find(node.input_types().begin(), node.input_types().end(), DT_RESOURCE) != node.input_types().end() || std::find(node.output_types().begin(), node.output_types().end(), DT_RESOURCE) != node.output_types().end(); }
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Feb 29 08:39:39 UTC 2024 - 21.3K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/transforms/lower_tf.cc
auto op = cast<SpaceToBatchNDOp>(src_op); Location loc = op.getLoc(); auto input_type = mlir::cast<TensorType>(op.getInput().getType()); auto element_type = input_type.getElementType(); if (!input_type.hasStaticShape()) { return failure(); } ArrayRef<int64_t> input_shape = input_type.getShape(); auto block_shape_type = mlir::cast<TensorType>(op.getBlockShape().getType());
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 74.9K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/python/converter_python_api.cc
const tflite::TensorType input_type = FromTocoDataTypeToTflitToTensorType(input_data_type); const tflite::TensorType output_type = FromTocoDataTypeToTflitToTensorType(output_data_type); std::string output_model; const absl::string_view input_model_buffer(buf, length); auto status = mlir::lite::QuantizeModel( input_model_buffer, input_type, output_type, inference_tensor_type,
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Jun 12 23:15:24 UTC 2024 - 19.2K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/transforms/legalize_tf.cc
// Create a tfl.transpose op that performs ZX transpose on `input`. auto create_z_x_transpose_op = [&](Value input) -> Value { RankedTensorType input_type = mlir::cast<RankedTensorType>(input.getType()); const int input_rank = input_type.getRank(); // Create a 1D I32 tensor for representing the dimension permutation. auto permuation_tensor_type =
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon May 20 20:06:54 UTC 2024 - 45.2K bytes - Viewed (0) -
tensorflow/compiler/jit/partially_decluster_pass.cc
// hostmem output. These nodes should be cloned to outside the cluster to // avoid the device-host copy we'd otherwise need. MemoryTypeVector input_mtypes, output_mtypes; for (Node* n : post_order) { std::optional<absl::string_view> from_cluster = GetXlaClusterForNode(*n); if (!from_cluster) { continue; }
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri Feb 09 11:36:41 UTC 2024 - 15.7K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/transforms/shape_inference.cc
TypeRange input_types, ArrayRef<func::FuncOp> functions, int64_t max_iterations); // Propagates shapes to regions given the shapes of the inputs of the regions. // All regions provided in `regions` are assumed to have inputs of type // `input_types`.
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Sat Jun 08 07:28:49 UTC 2024 - 134.1K bytes - Viewed (0)