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Results 31 - 40 of 171 for Bias (0.09 sec)
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src/math/ldexp.go
exp += e x := Float64bits(frac) exp += int(x>>shift)&mask - bias if exp < -1075 { return Copysign(0, frac) // underflow } if exp > 1023 { // overflow if frac < 0 { return Inf(-1) } return Inf(1) } var m float64 = 1 if exp < -1022 { // denormal exp += 53 m = 1.0 / (1 << 53) // 2**-53 } x &^= mask << shift x |= uint64(exp+bias) << shift return m * Float64frombits(x)
Registered: Wed Jun 12 16:32:35 UTC 2024 - Last Modified: Thu Oct 19 11:59:09 UTC 2023 - 1.1K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/stablehlo/passes/bridge/optimize.td
def optimizeConsecutiveConv#OpsTuple[0]#OpsTuple[1] : Pat< (OpsTuple[1] (OpsTuple[0] $input, $zp_offset, $broadcast_dims_1), $bias, $broadcast_dims_2), (OpsTuple[0] $input, (OpsTuple[2] $zp_offset, $bias, $broadcast_dims_2), $broadcast_dims_1), [ (IsNull $broadcast_dims_1), (IsNull $broadcast_dims_2), (TensorOf<[AnyInteger]> $input),
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Sat Feb 24 02:26:47 UTC 2024 - 2K bytes - Viewed (0) -
src/strconv/atof.go
} // Our range is [0.5,1) but floating point range is [1,2). exp-- // Minimum representable exponent is flt.bias+1. // If the exponent is smaller, move it up and // adjust d accordingly. if exp < flt.bias+1 { n := flt.bias + 1 - exp d.Shift(-n) exp += n } if exp-flt.bias >= 1<<flt.expbits-1 { goto overflow } // Extract 1+flt.mantbits bits. d.Shift(int(1 + flt.mantbits))
Registered: Wed Jun 12 16:32:35 UTC 2024 - Last Modified: Mon Jun 06 18:50:50 UTC 2022 - 15.9K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/stablehlo/tests/pipelines/process_nchw_tensor.mlir
// CHECK: return %[[TRANSPOSE_1]] // ----- // Tests that a `add(convolution(%activation, %weight), %bias)` pattern with the // activation tensor of NCHW format and non-constant bias is converted to NHWC // convolution, but without the deferred transpose for `stablehlo.add`. // Transpose ops are inserted to the activation and output of
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 18 20:32:46 UTC 2024 - 12.6K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/common/quantization_lib/quantization.td
// Specify this trait if the bias-th input of the op is a bias input, which // needs a scale based on the scales of op1 and op2. class AccumulatorUniformScale<int bias, int op1, int op2> : NativeOpTrait< !strconcat("quant::AccumulatorUniformScale<", !interleave([bias, op1, op2], ", "), ">::Impl")>;
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Mar 05 07:39:40 UTC 2024 - 8.3K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/transforms/quantize_patterns.td
def FoldQuantWeightsIntoTposeConv : Pat< (TFL_TransposeConvOp $output_shape, (TFL_DequantizeOp $quant_weights), $quant_input, $bias, $padding, $stride_h, $stride_w, $faf), (TFL_TransposeConvOp $output_shape, $quant_weights, $quant_input, $bias, $padding, $stride_h, $stride_w, $faf),
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue May 28 23:10:13 UTC 2024 - 2.3K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/quantization/tensorflow/fallback_to_flex_patterns.td
// Keeps Add and Sub ops if the second operand is bias. def KeepAddV2Op : Pat< (TF_AddV2Op:$add_op $input, (TF_ConstOp:$bias_cst $bias)), (MarkNoFallback (TF_AddV2Op $input, $bias_cst)), [(IsFusibleWithBias $input), (RankEquals<"1"> $bias_cst), (NoFallbackAttrNotSet $add_op)]>; def KeepSubOp : Pat< (TF_SubOp:$sub_op $input, (TF_ConstOp:$bias_cst $bias)), (MarkNoFallback (TF_SubOp $input, $bias_cst)),
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Sep 29 21:02:21 UTC 2022 - 3.2K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/tensorflow/tests/quantize_xla.mlir
%weight = arith.constant dense_resource<__elided__> : tensor<2x3x3x2xf32> %bias = arith.constant dense<[7.11401462, 7.05456924]> : tensor<2xf32> %q_input= "quantfork.qcast"(%input) : (tensor<1x3x4x3xf32>) -> tensor<1x3x4x3x!quant.uniform<i8:f32, 0.58810077742034317:-128>>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed May 08 19:32:28 UTC 2024 - 11.4K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/common/quantization_lib/quantization_driver.h
// constant is used by multiple ops as a bias, duplicate constants and // let each op assign its own quantization parameter for bias. // - Adds all the non-bias constants (weights) to a set for looking up // later. // - Adds all per-channel weights to a set for looking up later. void PreprocessConstantOps();
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Mar 20 11:42:17 UTC 2024 - 16.8K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/stablehlo/python/integration_test/quantize_model_test_base.py
bias_fn: Optional[ops.Operation] = None, activation_fn: Optional[ops.Operation] = None, ) -> module.Module: class MatmulModel(module.Module): """A simple model with a single matmul. Bias and activation function are optional. """ def __init__( self, weight_shape: Sequence[int], ) -> None: """Initializes a MatmulModel. Args:
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue May 14 06:31:57 UTC 2024 - 18.2K bytes - Viewed (0)