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Results 31 - 40 of 184 for output_types (0.2 sec)
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tensorflow/compiler/mlir/quantization/common/quantization_lib/quantization_utils.h
} // Collect all the quantized outputs and replace them by the results of // the new quantized op. llvm::SmallDenseMap<Value, int> outputs_replaced; SmallVector<Type, 4> output_types; output_types.reserve(quantizing_op->getNumResults()); for (const auto& enumerated_result : llvm::enumerate(quantizing_op->getResults())) { Value result = enumerated_result.value();
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Apr 24 20:30:06 UTC 2024 - 41.7K bytes - Viewed (0) -
tensorflow/compiler/jit/xla_cluster_util.cc
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(); } void RemoveFromXlaCluster(NodeDef* node_def) { node_def->mutable_attr()->erase(kXlaClusterAttr); }
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/jit/build_xla_ops_pass.cc
MemoryTypeVector input_mtypes, output_mtypes; DeviceType device_type(""); TF_RETURN_IF_ERROR( DeviceNameToDeviceType(n->assigned_device_name(), &device_type)); TF_RETURN_IF_ERROR(MemoryTypesForNode(root.graph()->op_registry(), device_type, n->def(), &input_mtypes, &output_mtypes)); return output_mtypes; }
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Mar 12 06:33:33 UTC 2024 - 24.3K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/transforms/unroll_batch_matmul.cc
SmallVector<int64_t, 3> slice_size = {1, num_rows, num_cols}; Type slice_result_type = RankedTensorType::get(slice_size, element_type); llvm::SmallVector<Type, 4> output_types(batch_size, slice_result_type); auto split_op = rewriter.create<TF::SplitOp>(loc, output_types, split_dimension_op.getOutput(), reshape_op.getOutput());
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 11.6K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/tensorflow/passes/insert_custom_aggregation_ops.cc
"max_percentile", rewriter.getF32FloatAttr( calib_opts_.calibration_parameters().max_percentile())), }; SmallVector<Type, 4> output_types{ value.getType(), RankedTensorType::get({}, rewriter.getF32Type()), RankedTensorType::get({}, rewriter.getF32Type()),
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri May 17 17:58:54 UTC 2024 - 14.8K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/tests/decompose_optionals.mlir
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Jun 12 21:18:05 UTC 2024 - 4.5K bytes - Viewed (0) -
tensorflow/cc/framework/cc_op_gen_util.h
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Feb 26 00:57:05 UTC 2024 - 4.6K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/tests/functional-control-flow-to-regions.mlir
finalize_func = @finalize, init_func = @init, next_func = @next, operandSegmentSizes = array<i32: 1, 2, 1>, output_shapes = [#tf_type.shape<>], output_types = [!tf_type.string], metadata = ""} : ( tensor<4xf32>, tensor<3xf32>, tensor<!tf_type.resource>, tensor<2xf32>) -> tensor<!tf_type.variant> return
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Nov 06 21:59:28 UTC 2023 - 11.9K bytes - Viewed (0) -
tensorflow/compiler/mlir/tfrt/tests/mlrt/tf_to_mlrt.mlir
%2 = "tf.Const"() {__op_key = 2: i32, device = "/device:CPU:0", value = dense<1> : tensor<i64>} : () -> tensor<i64> %3 = "tf.RangeDataset"(%0, %1, %2) {__op_key = 3: i32, device = "/device:CPU:0", output_shapes = [#tf_type.shape<>], output_types = [i64], metadata = ""} : (tensor<i64>, tensor<i64>, tensor<i64>) -> tensor<!tf_type.variant> // CHECK: tf_mlrt.executeop{{.*}}op: \22FlatMapDataset\22 // CHECK-SAME: \22__inference_Dataset_flat_map_lambda_19\22
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri May 31 20:44:15 UTC 2024 - 24.7K bytes - Viewed (0) -
tensorflow/compiler/mlir/tf2xla/internal/passes/extract_outside_compilation.cc
for (Value v : inputs) operand_types.emplace_back(v.getType()); llvm::SmallVector<Type, 4> output_types; output_types.reserve(outputs.size()); for (Value v : outputs) output_types.emplace_back(v.getType()); auto func_type = builder->getFunctionType(operand_types, output_types); FuncOp outlined_func = FuncOp::create(ops.front()->getLoc(), kHostFunctionAttr, func_type);
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Apr 30 21:25:12 UTC 2024 - 68.3K bytes - Viewed (0)