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Results 171 - 180 of 203 for dequantize (0.22 sec)
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tensorflow/compiler/mlir/lite/quantization/lite/quantize_weights.cc
mlir::TFL::PassConfig(quant_specs), pm); if (failed(pm.run(module.get()))) { absl::string_view err = statusHandler.ConsumeStatus().message(); LOG(ERROR) << "Failed to quantize: " << err; return kTfLiteError; } // Export the results to the builder std::string result; tflite::FlatbufferExportOptions options; options.toco_flags.set_force_select_tf_ops(false);
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Jun 12 23:15:24 UTC 2024 - 9.5K bytes - Viewed (1) -
tensorflow/compiler/mlir/quantization/stablehlo/tests/passes/quantize_composite_functions_weight_only.mlir
// RUN: stablehlo-quant-opt %s -split-input-file -verify-diagnostics \ // RUN: -stablehlo-quantize-composite-functions | FileCheck --check-prefix=CHECK %s // Test that per-tensor weight-only quantized dot_general op is produced when // empty `weight_only_ptq` is provided. module attributes {tf_saved_model.semantics} { func.func private @quantize_dot_general_per_tensor(%arg0: tensor<1x2xf32>) -> tensor<1x3xf32> attributes {tf._original_func_name = "main_0"} {
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 09 05:56:10 UTC 2024 - 9.4K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/stablehlo/tests/passes/prepare_quantize/prepare_quantize.mlir
// RUN: stablehlo-quant-opt %s -split-input-file -stablehlo-prepare-quantize=enable-per-channel-quantized-weight=false -verify-diagnostics | FileCheck %s // ----- // CHECK-LABEL: func @dot // CHECK-SAME: (%[[ARG_0:.*]]: tensor<?x3xf32>) -> tensor<?x2xf32> func.func @dot(%arg0: tensor<?x3xf32>) -> tensor<?x2xf32> { // CHECK: %[[cst:.*]] = stablehlo.constant // CHECK: %[[q1:.*]] = "quantfork.qcast"(%[[cst]])
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Feb 22 19:52:06 UTC 2024 - 8.7K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/common/quantization_lib/quantization_utils.cc
// asymmetric range. For a state tensor, assigning correct quantization // parameters is sufficient, and for constants with asymmetric range it's // not correctly quantized by legacy quantizer so call the new Quantize. return Quantize(real_value, tensor_type); } else if (width == 16) { if (const auto uniform_type = dyn_cast<UniformQuantizedType>(q_type)) { const auto quantized_values =
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed May 08 02:10:16 UTC 2024 - 43.2K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/tensorflow/tests/quantize_composite_functions_drq.mlir
// RUN: tf-quant-opt %s -split-input-file -quant-insert-quantized-functions='quantization-method=drq target-opset=UNIFORM_QUANTIZED' -quant-quantize-composite-functions='quantization-method=drq target-opset=UNIFORM_QUANTIZED' -symbol-dce | FileCheck %s module { // TODO(b/260020937): Support transpose_a, transpose_b for matmul. func.func @matmul(%arg0: tensor<2x12xf32>) -> (tensor<*xf32>) {
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri Jan 05 18:35:42 UTC 2024 - 9.8K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/transforms/prepare_patterns.td
class UsedBy<string op> : Constraint< CPred<"llvm::isa<mlir::TFL::" # op # "Op>(*$0.getUsers().begin())">>; // When the op is passing-through, the output types of the quantized ops need // to be updated as well. Since the quantize op manages its own type by the // "qtype" attribute, we should update the type shape in this attribute. def ReorderTransposeDequantQuant : Pat<(TF_TransposeOp:$old_value
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Apr 30 00:40:15 UTC 2024 - 10.5K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tf_to_tfl_flatbuffer.cc
&q_builder, input_model, quantized_type, use_updated_hybrid_scheme, ::tflite::optimize::QuantizerType::OLD_QUANTIZER) != kTfLiteOk) { return absl::InvalidArgumentError( "Quantize weights transformation failed."); } const uint8_t* q_buffer = q_builder.GetBufferPointer(); *result = std::string(reinterpret_cast<const char*>(q_buffer), q_builder.GetSize());
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/quantization/stablehlo/tests/passes/lift_quantizable_spots_as_functions_with_quantization_specs.mlir
func.func @main(%arg0: tensor<1x2xf32>) -> tensor<1x2xf32> { %0 = stablehlo.add %arg0, %arg0 : tensor<1x2xf32> return %0 : tensor<1x2xf32> } // Tests that `composite_add_fn_1` does not quantize when quantizing // only compute-heavy ops. // STATIC-RANGE-PTQ-TO-COMPUTE-HEAVY: %[[CONST:.+]] = stablehlo.constant dense<2.000000e+00>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Apr 02 18:09:38 UTC 2024 - 8.1K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/transforms/passes.h
bool enable_dynamic_update_slice); std::unique_ptr<OperationPass<ModuleOp>> CreateLowerStaticTensorListPass(); // Creates an instance of the TensorFlow Lite dialect Quantize pass. // Use quant_specs.ops_blocklist and quant_specs.nodes_blocklist if possible // as they are now structure variables of QuantizationSpecs. std::unique_ptr<OperationPass<func::FuncOp>> CreateQuantizePass(
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Mar 07 21:29:34 UTC 2024 - 10.9K bytes - Viewed (0) -
src/log/log_test.go
} } func TestUTCFlag(t *testing.T) { var b strings.Builder l := New(&b, "Test:", LstdFlags) l.SetFlags(Ldate | Ltime | LUTC) // Verify a log message looks right in the right time zone. Quantize to the second only. now := time.Now().UTC() l.Print("hello") want := fmt.Sprintf("Test:%d/%.2d/%.2d %.2d:%.2d:%.2d hello\n", now.Year(), now.Month(), now.Day(), now.Hour(), now.Minute(), now.Second())
Registered: Wed Jun 12 16:32:35 UTC 2024 - Last Modified: Fri Apr 21 20:04:37 UTC 2023 - 7.4K bytes - Viewed (0)