- Sort Score
- Result 10 results
- Languages All
Results 11 - 20 of 85 for dequantize (0.25 sec)
-
tensorflow/compiler/mlir/lite/transforms/quantize_patterns.td
include "tensorflow/compiler/mlir/lite/ir/tfl_ops.td" // Quantize attribute $0 by using quantization parameter from %1. def QuantizeByQuantizedType : NativeCodeCall<"quant::Quantize($0, $1.getValue())">; def F32ElementsAttr : ElementsAttrBase< CPred<"$_self.cast<ElementsAttr>().getShapedType().getElementType().isF32()">, "float constant tensor">; // Squash tfl.dequantize and tfl.quantize pairs.
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue May 28 23:10:13 UTC 2024 - 2.3K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/tensorflow/ops/tf_quantize_op.h
// After applying the function, a quantize/dequantize functions are created // where the body of each function contains a specific quantization algorithm. // The input of the quantize function has one operand of // IsValueWithQuantizablePrecision and the output is a tensor with supported // quantized precision (like int8). For dequantize function, it is the other way // around.
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Sun Mar 24 07:44:40 UTC 2024 - 1.9K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/tensorflow/passes/propagate_quantize_type.cc
auto op_before_dequantize = original_dequantize_op.getOperand(0); // Create a new dequantize op that is propagated. rewriter.setInsertionPointAfter(user_op); TF::PartitionedCallOp new_dequantize_op = cast<TF::PartitionedCallOp>(rewriter.clone(*original_dequantize_op)); // Skip the original dequant op and connect the op before dequantize to the // user op. user_op->setOperand(user_idx, op_before_dequantize);
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 7K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/tensorflow/passes/post_quantize.cc
op->user_begin()->hasTrait<OpTrait::IsTerminator>()) return failure(); } // If the quantize op is a requantize op, it is being used in other scale // adjustments and should be kept. Instead, moving dequantize op before // the requantize op to remove the unnecessary requantize op. if (auto qtype = QuantizedType::getQuantizedElementType(q.getArg().getType())) {
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Mar 05 07:39:40 UTC 2024 - 5.6K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/mlir2flatbuffer/depthwise_conv2d_v2.mlir
// CHECK: { // CHECK-NEXT: version: 3, // CHECK-NEXT: operator_codes: [ { // CHECK-NEXT: deprecated_builtin_code: 6, // CHECK-NEXT: version: 1, // CHECK-NEXT: builtin_code: DEQUANTIZE // CHECK-NEXT: }, { // CHECK-NEXT: deprecated_builtin_code: 4, // CHECK-NEXT: version: 2, // CHECK-NEXT: builtin_code: DEPTHWISE_CONV_2D // CHECK-NEXT: } ], // CHECK-NEXT: subgraphs: [ {
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Jul 14 16:41:28 UTC 2022 - 9.1K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/tensorflow/utils/fake_quant_utils.h
// Finally, use the quantization parameter to create the quantize and // dequantize ops, and insert them between the tf.FakeQuantWithMinMaxVarsOp // and its users. auto quantize = rewriter.create<quantfork::QuantizeCastOp>( tf_op.getLoc(), qtype.getValue(), input); auto dequantize = rewriter.create<quantfork::DequantizeCastOp>( tf_op.getLoc(), res_type, quantize.getResult());
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 6.3K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/mlir2flatbuffer/depthwise_conv2d.mlir
// CHECK: { // CHECK-NEXT: version: 3, // CHECK-NEXT: operator_codes: [ { // CHECK-NEXT: deprecated_builtin_code: 6, // CHECK-NEXT: version: 1 // CHECK-NEXT: builtin_code: DEQUANTIZE // CHECK-NEXT: }, { // CHECK-NEXT: deprecated_builtin_code: 4, // CHECK-NEXT: version: 1 // CHECK-NEXT: builtin_code: DEPTHWISE_CONV_2D // CHECK-NEXT: } ], // CHECK-NEXT: subgraphs: [ {
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Jul 14 16:41:28 UTC 2022 - 9K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/stablehlo/passes/post_quantize.cc
if (!q->getAttr(kVolatileOpAttrName)) return failure(); // If the quantize op is a requantize op, it is being used in other scale // adjustments and should be kept. Instead, move dequantize op before the // requantize op to remove the unnecessary requantize op. if (const QuantizedType qtype = QuantizedType::getQuantizedElementType(q.getArg().getType())) {
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Mar 05 07:39:40 UTC 2024 - 6.3K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/utils/fake_quant_utils.cc
// and tfl.dequantize pairs before tf.FakeQuant* being foled. LogicalResult ConvertFakeQuantOps(func::FuncOp func, MLIRContext* ctx, bool use_fake_quant_num_bits) { OpBuilder builder(func); if (failed(UnwrapTFCustomOps(func, builder))) { return failure(); } // Insert the tfl.quantize/tfl.dequantize ops after the tf.FakeQuant* ops to
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Sat Jun 03 00:14:05 UTC 2023 - 4.3K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/experimental/tac/transforms/transform_patterns.td
(Arith_ConstantOp ConstantAttr<RankedF32ElementsAttr<[]>, "-1.0f">), TFL_AF_None), $act)>; // Squash tfl.dequantize and tfl.quantize pairs. // TODO(b/185915462): Compare the scale of input and output. This can also be // squashed to a requantize op if the scales are different.
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Sep 29 21:02:21 UTC 2022 - 1.4K bytes - Viewed (0)