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Results 1 - 10 of 4,138 for fusing (0.32 sec)
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tensorflow/compiler/mlir/tensorflow/transforms/fused_kernel_matcher.cc
// need/usage. File a bug to request porting over additional fusions. // TODO(b/158265178): Support GPU-specific fusions. // TODO(b/158266710): Support CPU MKL configurations. #define GEN_PASS_DEF_FUSEDKERNELMATCHERPASS #include "tensorflow/compiler/mlir/tensorflow/transforms/tf_passes.h.inc" // Optimizes TF computations by fusing subgraphs/nodes onto more efficient
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 14.9K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/stablehlo/passes/unwrap_xla_call_module_op.cc
private: void runOnOperation() override; }; void UnwrapXlaCallModuleOp(TF::XlaCallModuleOp call_op, SymbolTable& symbol_table) { // Do not inline lifted quantized functions used for fusing patterns. // TODO - b/310539922: Remove reference to TF/TFL utils. if (call_op->hasAttr(kQuantTraitAttrName)) { return; } auto function_name = call_op
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Mar 05 07:39:40 UTC 2024 - 4.8K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/tensorflow/passes/prepare_lifting.cc
return "quant-prepare-lifting"; } StringRef getDescription() const final { // This is a brief description of the pass. return "Apply graph optimizations such as fusing and constant folding to " "prepare lifting."; } void getDependentDialects(DialectRegistry& registry) const override { registry.insert<TF::TensorFlowDialect, arith::ArithDialect>(); }
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri May 17 17:58:54 UTC 2024 - 13.3K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tf_tfl_passes.cc
mlir::TFL::CreatePostQuantizePass(emit_quant_adaptor_ops)); } pass_manager.addNestedPass<mlir::func::FuncOp>( mlir::TFL::CreateOptimizeOpOrderPass()); // Add optimization pass after quantization for additional fusing // opportunities. if (!pass_config.unfold_batch_matmul) { // Enable an optimization pass that transforms FC to BatchMatmul only when // `unfold_batch_matmul=false`.
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Jun 06 18:45:51 UTC 2024 - 25.5K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/stablehlo/passes/quantization_patterns.h
// Safeguard check to ensure that there is at least one quantizable op. if (failed(candidate_ops) || candidate_ops->empty()) return failure(); // Rewrite the floating-point ops to the quantized version, by fusing // preceding dequantize ops and succeding quantize ops. for (Operation* candidate_op : *candidate_ops) { // If it is requantize op, we shouldn't rewrite this op.
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 10.9K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/optimize.mlir
func.return %7: tensor<1xf32> // Fusing-LABEL: FusingaddRelu // Fusing: %[[add:[0-9].*]] = tfl.add %arg0, %arg1 {fused_activation_function = "NONE"} : tensor<1xf32> // Fusing: %[[add1:[0-9].*]] = tfl.add %arg0, %[[add]] {fused_activation_function = "RELU"} : tensor<1xf32> // Fusing: %[[relu:[0-9].*]] = "tfl.relu"(%arg0) : (tensor<1xf32>) -> tensor<1xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 16 20:31:41 UTC 2024 - 284.1K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/tensorflow/passes/passes.h
std::unique_ptr<OperationPass<ModuleOp>> CreateLiftQuantizableSpotsAsFunctionsPass( const tensorflow::quantization::QuantizationOptions& quant_options); // Apply graph optimizations such as fusing and constant folding to prepare // lifting. std::unique_ptr<OperationPass<func::FuncOp>> CreatePrepareLiftingPass( tensorflow::quantization::OpSet target_opset);
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri May 10 04:07:09 UTC 2024 - 12.3K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/tensorflow/passes/quantize.cc
auto users = op.getResult().getUsers(); quantizing_ops.append(users.begin(), users.end()); bool changed = false; // Rewrite the floating-point ops to the quantized version, by fusing // preceding dequantize ops and succeding quantize ops. for (Operation* quantizing_op : quantizing_ops) { // If it is requantize op, we shouldn't rewrite this op.
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri Mar 22 05:52:39 UTC 2024 - 23.6K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/stablehlo/python/integration_test/quantize_model_test_base.py
data_format='NHWC', name='sample/conv', ) if bias_fn is not None: out = nn_ops.bias_add(out, self.bias) if has_batch_norm: # Fusing is supported for non-training case. out, _, _, _, _, _ = nn_ops.fused_batch_norm_v3( out, scale, offset, mean, variance, is_training=False ) if activation_fn is not None:
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue May 14 06:31:57 UTC 2024 - 18.2K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/tensorflow/python/integration_test/quantize_model_test_base.py
padding='SAME', data_format='NHWC', ) if has_bias: out = nn_ops.bias_add(out, self.bias) if has_batch_norm: # Fusing is supported for non-training case. out, _, _, _, _, _ = nn_ops.fused_batch_norm_v3( out, scale, offset, mean, variance, is_training=False ) if activation_fn is not None:
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Mar 21 08:51:46 UTC 2024 - 51.2K bytes - Viewed (0)