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Results 11 - 20 of 24 for numBits (0.23 sec)
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src/internal/coverage/decodemeta/decode.go
numUnits := uint32(d.r.ReadULEB128()) fnameidx := uint32(d.r.ReadULEB128()) fileidx := uint32(d.r.ReadULEB128()) f.Srcfile = d.strtab.Get(fileidx) f.Funcname = d.strtab.Get(fnameidx) // Now the units f.Units = f.Units[:0] if cap(f.Units) < int(numUnits) { f.Units = make([]coverage.CoverableUnit, 0, numUnits) } for k := uint32(0); k < numUnits; k++ {
Registered: Wed Jun 12 16:32:35 UTC 2024 - Last Modified: Tue May 23 11:36:28 UTC 2023 - 3.6K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/quantization/tensorflow/tests/tf_to_quant_4bit.mlir
%0 = "tf.FakeQuantWithMinMaxVars"(%arg0, %arg1, %arg2) {num_bits = 3, narrow_range = false} : (tensor<8xf32>, tensor<f32>, tensor<f32>) -> tensor<8xf32> %1 = "quantfork.qcast"(%0) : (tensor<8xf32>) -> tensor<8x!quant.uniform<i4:f32, 1.000000e+00:-8>> func.return %1 : tensor<8x!quant.uniform<i4:f32, 1.000000e+00:-8>> // CHECK: %0 = "tf.FakeQuantWithMinMaxVars"(%arg0, %cst, %cst_0) <{narrow_range = false, num_bits = 3 : i64}>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Oct 30 06:52:55 UTC 2023 - 9.4K bytes - Viewed (0) -
tensorflow/c/experimental/saved_model/core/ops/restore_ops_test.cc
"x/.ATTRIBUTES/VARIABLE_VALUE", DT_FLOAT, &x_handle)); AbstractTensorPtr x = testing::TensorHandleToTensor(x_handle.get()); EXPECT_EQ(x->Type(), DT_FLOAT); EXPECT_EQ(x->NumElements(), 1); EXPECT_EQ(x->NumDims(), 0); EXPECT_FLOAT_EQ(*reinterpret_cast<float*>(x->Data()), 1.0f); ImmediateTensorHandlePtr y_handle; TF_EXPECT_OK(internal::SingleRestore( context(), CheckpointPrefix("VarsAndArithmeticObjectGraph"),
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri Apr 14 19:16:58 UTC 2023 - 4.2K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/tensorflow/tests/fake_quant_e2e_xla.mlir
%0 = "tf.FakeQuantWithMinMaxArgs"(%arg0) {device = "", max = 2.000000e-01 : f32, min = -1.000000e-01 : f32, narrow_range = false, num_bits = 8 : i64} : (tensor<1x3x4x3xf32>) -> tensor<1x3x4x3xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Oct 30 06:52:55 UTC 2023 - 7.2K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/raise-custom-ops.mlir
// WRAPPED-NEXT: %[[fq:.*]] = "tf.FakeQuantWithMinMaxVarsPerChannel"(%arg1, %arg2, %arg3) <{narrow_range = true, num_bits = 8 : i64}> {device = ""} : (tensor<*xf32>, tensor<186xf32>, tensor<186xf32>) -> tensor<*xf32> // WRAPPED-NEXT: "tfl.yield"(%[[fq]]) : (tensor<*xf32>) -> () // WRAPPED-NEXT: }) {device = "", narrow_range = true, num_bits = 8 : i64} : (tensor<*xf32>, tensor<186xf32>, tensor<186xf32>) -> tensor<*xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Oct 30 06:52:55 UTC 2023 - 4K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/tensorflow/tests/fake_quant_e2e_flow.mlir
%0 = "tf.FakeQuantWithMinMaxArgs"(%arg1) {device = "", max = 2.000000e+00 : f32, min = -1.000000e+00 : f32, narrow_range = false, num_bits = 8 : i64} : (tensor<2x3x3x2xf32>) -> tensor<*xf32> %1 = "tf.FakeQuantWithMinMaxArgs"(%arg0) {device = "", max = 2.000000e-01 : f32, min = -1.000000e-01 : f32, narrow_range = false, num_bits = 8 : i64} : (tensor<1x3x4x3xf32>) -> tensor<*xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Oct 30 06:52:55 UTC 2023 - 3.5K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/utils/fake_quant_utils.h
quant_dim = mlir::cast<ShapedType>(res.getType()).getRank() - 1; } // Use the min/max from the operands and the num_bits and narrow_range // attribute to create the quantization parameter for the new quantize op. rewriter.setInsertionPointAfter(tf_op.getOperation()); IntegerAttr num_bits = rewriter.getI64IntegerAttr(tf_op.getNumBits()); BoolAttr narrow_range = rewriter.getBoolAttr(tf_op.getNarrowRange());
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 6.6K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/stablehlo/tests/legalize-skip-quantization-ops.mlir
func.func @fake_quant_with_min_max_vars(%arg0: tensor<1x1x28x48xf32>, %arg1: tensor<f32>, %arg2: tensor<f32>) -> tensor<1x1x28x48xf32> { %0 = "tf.FakeQuantWithMinMaxVars"(%arg0, %arg1, %arg2) {device = "", narrow_range = true, num_bits = 8 : i64} : (tensor<1x1x28x48xf32>, tensor<f32>, tensor<f32>) -> tensor<1x1x28x48xf32> func.return %0 : tensor<1x1x28x48xf32> // CHECK-SKIP: tf.FakeQuantWithMinMaxVars // CHECK-NOSKIP-NOT: tf.
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Dec 14 07:38:29 UTC 2022 - 676 bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/quantization/tensorflow/tf_to_quant.cc
quant_dim = mlir::cast<ShapedType>(res.getType()).getRank() - 1; } // Use the min/max from the operands and the num_bits and narrow_range // attribute to create the quantization parameter for the new quantize op. rewriter.setInsertionPointAfter(tf_op.getOperation()); IntegerAttr num_bits = rewriter.getI64IntegerAttr(tf_op.getNumBits()); BoolAttr narrow_range = rewriter.getBoolAttr(tf_op.getNarrowRange());
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 8.1K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/tensorflow/utils/fake_quant_utils.h
quant_dim = input_type.getRank() - 1; } // Use the min/max from the operands and the num_bits and narrow_range // attribute to create the quantization parameter for the new quantize op. rewriter.setInsertionPointAfter(tf_op.getOperation()); IntegerAttr num_bits = rewriter.getI64IntegerAttr(tf_op.getNumBits()); BoolAttr narrow_range = rewriter.getBoolAttr(tf_op.getNarrowRange());
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 6.3K bytes - Viewed (0)