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Results 11 - 20 of 58 for dequantize (0.18 sec)
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tensorflow/compiler/mlir/lite/tests/post-quantize-dynamic-range.mlir
// RUN: tf-opt %s -tfl-prepare-quantize-dynamic-range="enable-custom-op-quantization=CustomTestOp=1" -tfl-quantize="enable-dynamic-range-quantization=true enable-custom-op-weight-only=CustomTestOp=false" -tfl-post-quantize="enable-no-side-effect=CustomTestOp=false" | FileCheck --check-prefix=NotPrune %s
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 02 09:41:17 UTC 2024 - 11.4K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/decompose-hybrid-quantization.mlir
// CHECK-DAG: %[[VAL2:.+]] = "tfl.dequantize"(%[[VAL0]]) // CHECK-DAG: %[[VAL3:.+]] = "tfl.dequantize"(%[[VAL1]]) // CHECK-DAG: %[[VAL4:.+]] = "tfl.conv_2d"(%arg0, %[[VAL2]], %[[VAL3]]) <{dilation_h_factor = 1 : i32, dilation_w_factor = 1 : i32, fused_activation_function = "NONE", padding = "SAME", stride_h = 1 : i32, stride_w = 1 : i32}>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 02 09:41:17 UTC 2024 - 13.1K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/experimental/tac/tests/pick-subgraphs.mlir
%0 = "tfl.dequantize"(%arg0) {tac.device = "GPU", tac.inference_type = "FLOAT"} : (tensor<100x!quant.uniform<i8:f32, 2.000000e-01:-3>>) -> tensor<100xf32> %1 = "tfl.dequantize"(%arg1) {tac.device = "GPU", tac.inference_type = "FLOAT"} : (tensor<100x!quant.uniform<i8:f32, 2.000000e-01:-3>>) -> tensor<100xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 02 09:41:17 UTC 2024 - 24.3K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/transforms/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 = quant::QuantizedType::getQuantizedElementType( q.getInput().getType())) {
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 17.1K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/quantization/lite/quantize_weights_test.cc
const auto float_graph = model_->subgraphs()->Get(subgraph_idx); // The output graph should have an extra tensor from the added dequantize // op. ASSERT_EQ(quantized_graph->tensors()->size(), float_graph->tensors()->size() + 1); // Check that a dequantize op exists. int32_t dequant_input_idx = -1; int32_t dequant_output_idx = -1;
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Jun 12 23:15:24 UTC 2024 - 32.3K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/experimental/tac/tests/get-alternative-subgraph.mlir
// CHECK-DAG: %[[VAL_8:.*]] = "tfl.pseudo_const"(){{.*}}dense<[384, 128]> : tensor<2xi32> // CHECK: %[[VAL_9:.*]] = "tfl.dequantize"(%[[VAL_0]]) {tac.device = "GPU", tac.inference_type = "FLOAT"} : (tensor<384x512x!quant.uniform<i8:f32, 1.000000e-01>>) -> tensor<384x512xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 02 09:41:17 UTC 2024 - 20.1K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/stablehlo/passes/passes.td
"MLIR dump file name.">, Option<"merge_fusion_with_dequantize_", "merge-fusion-with-dequantize", "bool", /*default=*/"false", "Whether to merge quantized conv/dot_general fusion with subsequent dequantize.">, ]; let dependentDialects = [ "mlir::arith::ArithDialect", "mlir::stablehlo::StablehloDialect", "mlir::quant::QuantizationDialect",
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue May 14 06:31:57 UTC 2024 - 10.3K bytes - Viewed (0) -
tensorflow/compiler/mlir/tf2xla/tests/legalize-tf-quant.mlir
// CHECK: %[[DEQUANTIZE:.*]] = mhlo.uniform_dequantize %[[CONVERT_2]] : (tensor<2x!quant.uniform<i8:f32, 1.000000e+00:3>>) -> tensor<2xf32> // CHECK: return %[[DEQUANTIZE]] : tensor<2xf32> %0 = "tf.UniformQuantize"(%arg0, %scales, %zps) { quantization_axis = -1 : i64, quantization_min_val = -128 : i64, quantization_max_val = 127 : i64
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 09 01:25:29 UTC 2024 - 37.3K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/common/quantization_lib/quantization_utils.h
// correct float op should be the user of the last DequantizeOp. if (llvm::isa<QuantizeOpT>(user)) { user = *user->getResult(0).getUsers().begin(); } if (auto dequantize = llvm::dyn_cast<DequantizeOpT>(user)) { // Replace all uses, except not quantizable ops that are being used in // the float backbone.
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/mlir/lite/tests/modify_io_nodes.mlir
%6 = "tfl.dequantize"(%5) : (tensor<1x401408x!quant.uniform<i8:f32, 3.906250e-03>>) -> tensor<1x401408xf32> func.return %6 : tensor<1x401408xf32> // CHECK-LABEL: func @modified(%arg0: tensor<1x224x224x3xf32>) -> tensor<1x401408xf32> // CHECK-NEXT: %[[shape:.*]] = arith.constant dense<[1, 401408]> : tensor<2xi32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 02 09:41:17 UTC 2024 - 19.9K bytes - Viewed (0)