/aosp_15_r20/external/pytorch/torch/testing/_internal/ |
H A D | common_pruning.py | 57 nn.Linear(7, 5, bias=False), 58 nn.Linear(5, 6, bias=False), 59 nn.Linear(6, 4, bias=False), 61 self.linear1 = nn.Linear(4, 4, bias=False) 62 self.linear2 = nn.Linear(4, 10, bias=False) 73 wrapped in a Sequential. Used to test pruned Linear-Bias-Linear fusion.""" 78 nn.Linear(7, 5, bias=True), 79 nn.Linear(5, 6, bias=False), 80 nn.Linear(6, 3, bias=True), 81 nn.Linear(3, 3, bias=True), [all …]
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/aosp_15_r20/external/pytorch/test/inductor/ |
H A D | test_cpu_select_algorithm.py | 152 @parametrize("bias", (True, False)) 156 self, batch_size, in_features, out_features, bias, input_3d, dtype argument 159 def __init__(self, bias): argument 161 self.linear = torch.nn.Linear(in_features, out_features, bias) 167 mod = M(bias=bias).to(dtype=dtype).eval() 187 @parametrize("bias", (True,)) 191 def test_linear_wgt_multi_users(self, in_features, out_features, bias, dtype): argument 193 def __init__(self, bias): argument 196 self.linear = torch.nn.Linear(in_features, out_features, bias) 204 mod = M(bias=bias).to(dtype=dtype).eval() [all …]
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/aosp_15_r20/external/pytorch/benchmarks/static_runtime/ |
H A D | test_generated_ops.cc | 18 %bias: None = prim::Constant() in TEST() 20 %cloned = aten::clone(%ret, %bias) in TEST() 48 %bias: None = prim::Constant() in TEST() 50 %cloned = aten::clone(%ret, %bias) in TEST() 78 %bias: None = prim::Constant() in TEST() 80 %cloned = aten::clone(%ret, %bias) in TEST() 108 %bias: None = prim::Constant() in TEST() 110 %cloned = aten::clone(%ret, %bias) in TEST() 138 %bias: None = prim::Constant() in TEST() 140 %cloned = aten::clone(%ret, %bias) in TEST() [all …]
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/aosp_15_r20/external/pytorch/test/ |
H A D | test_stateless.py | 32 self.tied_bias = self.l1.bias 45 bias = torch.tensor([0.0], device=device) 49 f'{prefix}.l1.bias': bias, 53 'l1.bias': bias, 157 bias = torch.tensor([0.0], requires_grad=True) 160 'l1.bias': bias, 166 self.assertIsNotNone(bias.grad) 170 self.assertIsNone(module.l1.bias.grad) 204 bias = torch.tensor([0.0]) 207 'l1.bias': bias, [all …]
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H A D | test_mkldnn_fusion.py | 65 def __init__(self, in_channels, out_channels, bias, **kwargs): argument 67 self.conv = torch.nn.Conv2d(in_channels, out_channels, bias=bias, **kwargs) 82 for bias, dilation, groups in options: 87 bias, 104 def __init__(self, unary_fn, in_channels, out_channels, bias, **kwargs): argument 106 self.conv = torch.nn.Conv2d(in_channels, out_channels, bias=bias, **kwargs) 119 for bias in [True, False]: 121 … m = M(unary_fn, 3, oC, bias, kernel_size=(3, 3)).to(memory_format=memory_format) 133 def __init__(self, m, in_channels, out_channels, bias, **kwargs): argument 135 self.conv = m(in_channels, out_channels, bias=bias, **kwargs) [all …]
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/aosp_15_r20/external/ComputeLibrary/tests/validation/fixtures/ |
H A D | GEMMFixture.h | 269 TensorType bias = create_tensor<TensorType>(bias_shape, data_type, 1); in compute_target() local 281 …gemm.configure(gpu_arch, lhs.info(), rhs.info(), bias.info(), dst.info(), alpha, beta, false, resh… in compute_target() 285 ARM_COMPUTE_ASSERT(bias.info()->is_resizable()); in compute_target() 287 add_padding_x({ &lhs, &rhs, &bias, &dst }); in compute_target() 292 bias.allocator()->allocate(); in compute_target() 297 ARM_COMPUTE_ASSERT(!bias.info()->is_resizable()); in compute_target() 303 fill(AccessorType(bias), 2); in compute_target() 308 { ACL_SRC_2, &bias }, in compute_target() 326 SimpleTensor<T> bias{ dst_shape, data_type, 1 }; in compute_reference() 335 fill(bias, 2); in compute_reference() [all …]
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/aosp_15_r20/external/pytorch/torch/ao/nn/intrinsic/qat/modules/ |
H A D | conv_fused.py | 55 bias, argument 87 if bias: 88 self.bias = Parameter(torch.empty(out_channels)) 90 self.register_parameter("bias", None) 111 init.zeros_(self.bn.bias) 113 if self.bias is not None: 116 init.uniform_(self.bias, -bound, bound) 150 # using zero bias here since the bias for original conv 152 if self.bias is not None: 153 zero_bias = torch.zeros_like(self.bias, dtype=input.dtype) [all …]
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/aosp_15_r20/external/tensorflow/tensorflow/lite/kernels/ |
H A D | fully_connected.cc | 135 const TfLiteTensor* bias, TfLiteTensor* output, in CheckTypes() argument 144 // optional bias tensor. in CheckTypes() 145 const bool is_optional_bias_float = !bias || (bias->type == kTfLiteFloat32); in CheckTypes() 147 !bias || (bias->type == kTfLiteInt32) || (bias->type == kTfLiteInt64); in CheckTypes() 210 const TfLiteTensor* bias = in PrepareImpl() local 220 CheckTypes(context, input, filter, bias, output, params)); in PrepareImpl() 257 if (bias) { in PrepareImpl() 258 TF_LITE_ENSURE_EQ(context, NumElements(bias), SizeOfDimension(filter, 0)); in PrepareImpl() 268 context, input, filter, bias, output, &real_multiplier)); in PrepareImpl() 479 const TfLiteTensor* bias, TfLiteTensor* output) { in EvalPie() argument [all …]
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/aosp_15_r20/external/pytorch/aten/src/ATen/native/ |
H A D | Convolution.cpp | 370 …d(const at::Tensor& input, const at::Tensor& weight, const std::optional<at::Tensor>& bias) const { in use_cpu_depthwise3x3_winograd() 386 (!bias.has_value() || bias->is_contiguous()) && in use_cpu_depthwise3x3_winograd() 657 const c10::ArrayRef<T>& weight_sizes, const at::Tensor& bias, in check_shape_forward() argument 694 …TORCH_CHECK(!bias.defined() || (bias.ndimension() == 1 && at::symint::size<T>(bias, 0) == weight_s… in check_shape_forward() 696 ", expected bias to be 1-dimensional with ", weight_sizes[0], " elements", in check_shape_forward() 697 ", but got bias of size ", at::symint::sizes<T>(bias), " instead"); in check_shape_forward() 730 …TORCH_CHECK(!bias.defined() || (bias.ndimension() == 1 && at::symint::size<T>(bias, 0) == weight_s… in check_shape_forward() 732 ", expected bias to be 1-dimensional with ", weight_sizes[1] * groups, " elements", in check_shape_forward() 733 ", but got bias of size ", at::symint::sizes<T>(bias), " instead"); in check_shape_forward() 742 check_shape_forward<T>(input, weight_sizes, /*bias=*/ Tensor(), params); in check_shape_backward() [all …]
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/aosp_15_r20/external/pytorch/torch/nn/modules/ |
H A D | linear.py | 60 bias: If set to ``False``, the layer will not learn an additive bias. 74 bias: the learnable bias of the module of shape :math:`(\text{out\_features})`. 75 If :attr:`bias` is ``True``, the values are initialized from 97 bias: bool = True, 108 if bias: 109 self.bias = Parameter(torch.empty(out_features, **factory_kwargs)) 111 self.register_parameter("bias", None) 119 if self.bias is not None: 122 init.uniform_(self.bias, -bound, bound) 125 return F.linear(input, self.weight, self.bias) [all …]
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H A D | conv.py | 49 __annotations__ = {'bias': Optional[torch.Tensor]} 51 …def _conv_forward(self, input: Tensor, weight: Tensor, bias: Optional[Tensor]) -> Tensor: # type:… 66 bias: Optional[Tensor] 78 bias: bool, 134 if bias: 135 self.bias = Parameter(torch.empty(out_channels, **factory_kwargs)) 137 self.register_parameter('bias', None) 146 if self.bias is not None: 150 init.uniform_(self.bias, -bound, bound) 163 if self.bias is None: [all …]
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/aosp_15_r20/external/tensorflow/tensorflow/compiler/xla/service/gpu/ |
H A D | gemm_rewriter.cc | 64 // If the bias is a sequence of ops that depend only on broadcasts of 65 // constants, materialize the bias if it's small. 67 // Normally the constant-folding pass would materialize the bias if it is 68 // calculated entirely from constants. But if the bias is a broadcast of a 80 // broadcasted bias, if it supports that fusion efficiently. 81 HloInstruction *MaybeConstantFoldBias(HloInstruction *bias) { in MaybeConstantFoldBias() argument 97 if (ShapeUtil::ByteSizeOf(bias->shape()) <= kMaxMaterializeBiasBytes && in MaybeConstantFoldBias() 98 (Match(bias, broadcast_of_nonscalar) || in MaybeConstantFoldBias() 99 Match(bias, m::Reshape(broadcast_of_nonscalar)) || in MaybeConstantFoldBias() 100 Match(bias, m::Transpose(broadcast_of_nonscalar)) || in MaybeConstantFoldBias() [all …]
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/aosp_15_r20/external/trusty/arm-trusted-firmware/plat/imx/imx8ulp/upower/ |
D | upower_soc_defs.h | 126 #define UPWR_FILL_DOMBIAS_ARGS(dom, bias, args) \ argument 129 switch ((bias)->apply) { \ 150 (args).B.dommode = (uint32_t)((bias)->dommode); \ 151 (args).B.avdmode = (uint32_t)((bias)->avdmode); \ 153 (args).B.domrbbn = ((bias)->dombias.rbbn > sat) ? sat : \ 154 UPWR_BIAS_MILIV((bias)->dombias.rbbn); \ 155 (args).B.domrbbp = ((bias)->dombias.rbbp > sat) ? sat : \ 156 UPWR_BIAS_MILIV((bias)->dombias.rbbp); \ 157 (args).B.avdrbbn = ((bias)->avdbias.rbbn > sat) ? sat : \ 158 UPWR_BIAS_MILIV((bias)->avdbias.rbbn); \ [all …]
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/aosp_15_r20/external/arm-trusted-firmware/fdts/ |
H A D | stm32mp15-pinctrl.dtsi | 24 bias-disable; 30 bias-pull-up; 38 bias-disable; 47 bias-disable; 59 bias-disable; 65 bias-pull-up; 77 bias-disable; 83 bias-pull-up; 98 bias-disable; 104 bias-disable; [all …]
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/aosp_15_r20/external/trusty/arm-trusted-firmware/fdts/ |
D | stm32mp15-pinctrl.dtsi | 25 bias-disable; 31 bias-pull-up; 40 bias-disable; 50 bias-disable; 63 bias-disable; 76 bias-disable; 86 bias-pull-up; 96 bias-pull-up; 112 bias-disable; 118 bias-disable; [all …]
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/aosp_15_r20/external/pytorch/torch/ao/pruning/_experimental/pruner/ |
H A D | prune_functions.py | 4 Also contains utilities for bias propagation 16 # BIAS PROPAGATION 31 r"""Returns new adjusted bias for the second supported module""" 44 # Propagating first layer pruned biases and calculating the new second layer bias 46 # so adding bias involves broadcasting, logically: 67 ): # next_layer is parametrized & has original bias ._bias 70 not parametrize.is_parametrized(next_layer) and next_layer.bias is not None 71 ): # next_layer not parametrized & has .bias 72 adjusted_bias = nn.Parameter(scaled_biases + next_layer.bias) 73 else: # next_layer has no bias [all …]
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/aosp_15_r20/external/pytorch/aten/src/ATen/native/vulkan/ops/ |
H A D | Mm.cpp | 155 Tensor bias = *bias_arg; in pack_biases() local 156 if (bias.is_cpu()) { in pack_biases() 157 bias = bias.vulkan(); in pack_biases() 159 return convert(bias); in pack_biases() 182 const Tensor bias = bias_arg->contiguous(); in pack_biases_quantized_weights() local 183 const IntArrayRef b_sizes = bias.sizes(); in pack_biases_quantized_weights() 184 const float* const src_bias_ptr = bias.const_data_ptr<float>(); in pack_biases_quantized_weights() 191 if (bias.sizes().size() == 3) { in pack_biases_quantized_weights() 195 } else if (bias.sizes().size() == 2) { in pack_biases_quantized_weights() 208 if (bias.sizes().size() == 2) { in pack_biases_quantized_weights() [all …]
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/aosp_15_r20/hardware/invensense/65xx/libsensors_iio/software/core/mllite/ |
H A D | data_builder.c | 56 void inv_apply_calibration(struct inv_single_sensor_t *sensor, const long *bias); 480 /** Takes raw data stored in the sensor, removes bias, and converts it to 483 * @param[in] bias bias in the mounting frame, in hardware units scaled by 486 void inv_apply_calibration(struct inv_single_sensor_t *sensor, const long *bias) in inv_apply_calibration() argument 497 raw32[0] -= bias[0] >> 1; in inv_apply_calibration() 498 raw32[1] -= bias[1] >> 1; in inv_apply_calibration() 499 raw32[2] -= bias[2] >> 1; in inv_apply_calibration() 506 /** Returns the current bias for the compass 507 * @param[out] bias Compass bias in hardware units scaled by 2^16. In mounting frame. 510 void inv_get_compass_bias(long *bias) in inv_get_compass_bias() argument [all …]
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/aosp_15_r20/external/pytorch/torch/ao/nn/quantizable/modules/ |
H A D | activation.py | 38 bias: add bias as module parameter. Default: True. 39 add_bias_kv: add bias to the key and value sequences at dim=0. 67 bias: bool = True, 81 bias, 90 self.embed_dim, self.embed_dim, bias=bias, **factory_kwargs 93 self.kdim, self.embed_dim, bias=bias, **factory_kwargs 96 self.vdim, self.embed_dim, bias=bias, **factory_kwargs 99 …self.out_proj = nn.Linear(self.embed_dim, self.embed_dim, bias=bias, **factory_kwargs) # type: ig… 138 observed.out_proj.bias = other.out_proj.bias # type: ignore[has-type] 141 bias = other.in_proj_bias [all …]
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/aosp_15_r20/system/chre/chre_api/legacy/v1_3/chre/ |
H A D | sensor.h | 239 * field within 'readings', or by the 3D array 'bias' (bias[0] == x_bias; 240 * bias[1] == y_bias; bias[2] == z_bias). Bias is subtracted from uncalibrated 246 * If bias delivery is supported, this event is generated by default when 248 * CHRE_SENSOR_TYPE_GYROSCOPE, or if bias delivery is explicitly enabled 258 * field within 'readings', or by the 3D array 'bias' (bias[0] == x_bias; 259 * bias[1] == y_bias; bias[2] == z_bias). Bias is subtracted from uncalibrated 265 * If bias delivery is supported, this event is generated by default when 267 * CHRE_SENSOR_TYPE_GEOMAGNETIC_FIELD, or if bias delivery is explicitly enabled 277 * field within 'readings', or by the 3D array 'bias' (bias[0] == x_bias; 278 * bias[1] == y_bias; bias[2] == z_bias). Bias is subtracted from uncalibrated [all …]
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/aosp_15_r20/system/chre/chre_api/legacy/v1_4/chre/ |
H A D | sensor.h | 240 * field within 'readings', or by the 3D array 'bias' (bias[0] == x_bias; 241 * bias[1] == y_bias; bias[2] == z_bias). Bias is subtracted from uncalibrated 247 * If bias delivery is supported, this event is generated by default when 249 * CHRE_SENSOR_TYPE_GYROSCOPE, or if bias delivery is explicitly enabled 259 * field within 'readings', or by the 3D array 'bias' (bias[0] == x_bias; 260 * bias[1] == y_bias; bias[2] == z_bias). Bias is subtracted from uncalibrated 266 * If bias delivery is supported, this event is generated by default when 268 * CHRE_SENSOR_TYPE_GEOMAGNETIC_FIELD, or if bias delivery is explicitly enabled 278 * field within 'readings', or by the 3D array 'bias' (bias[0] == x_bias; 279 * bias[1] == y_bias; bias[2] == z_bias). Bias is subtracted from uncalibrated [all …]
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/aosp_15_r20/hardware/invensense/6515/libsensors_iio/software/core/mllite/ |
H A D | data_builder.c | 57 void inv_apply_calibration(struct inv_single_sensor_t *sensor, const long *bias); 685 /** Takes raw data stored in the sensor, removes bias, and converts it to 688 * @param[in] bias bias in the mounting frame, in hardware units scaled by 691 void inv_apply_calibration(struct inv_single_sensor_t *sensor, const long *bias) in inv_apply_calibration() argument 702 raw32[0] -= bias[0] >> 1; in inv_apply_calibration() 703 raw32[1] -= bias[1] >> 1; in inv_apply_calibration() 704 raw32[2] -= bias[2] >> 1; in inv_apply_calibration() 711 /** Returns the current bias for the compass 712 * @param[out] bias Compass bias in hardware units scaled by 2^16. In mounting frame. 715 void inv_get_compass_bias(long *bias) in inv_get_compass_bias() argument [all …]
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/aosp_15_r20/external/pytorch/torch/_inductor/ |
H A D | mkldnn_lowerings.py | 73 bias: TensorBox, 86 bias, 102 bias: TensorBox, 118 bias, 136 bias: TensorBox, 152 bias, 297 bias: TensorBox, 311 bias, 372 bias: TensorBox, 392 bias, [all …]
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/aosp_15_r20/system/chre/chre_api/legacy/v1_6/chre/ |
H A D | sensor.h | 274 * field within 'readings', or by the 3D array 'bias' (bias[0] == x_bias; 275 * bias[1] == y_bias; bias[2] == z_bias). Bias is subtracted from uncalibrated 281 * If bias delivery is supported, this event is generated by default when 283 * CHRE_SENSOR_TYPE_GYROSCOPE, or if bias delivery is explicitly enabled 293 * field within 'readings', or by the 3D array 'bias' (bias[0] == x_bias; 294 * bias[1] == y_bias; bias[2] == z_bias). Bias is subtracted from uncalibrated 300 * If bias delivery is supported, this event is generated by default when 302 * CHRE_SENSOR_TYPE_GEOMAGNETIC_FIELD, or if bias delivery is explicitly enabled 312 * field within 'readings', or by the 3D array 'bias' (bias[0] == x_bias; 313 * bias[1] == y_bias; bias[2] == z_bias). Bias is subtracted from uncalibrated [all …]
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/aosp_15_r20/system/chre/chre_api/legacy/v1_5/chre/ |
H A D | sensor.h | 274 * field within 'readings', or by the 3D array 'bias' (bias[0] == x_bias; 275 * bias[1] == y_bias; bias[2] == z_bias). Bias is subtracted from uncalibrated 281 * If bias delivery is supported, this event is generated by default when 283 * CHRE_SENSOR_TYPE_GYROSCOPE, or if bias delivery is explicitly enabled 293 * field within 'readings', or by the 3D array 'bias' (bias[0] == x_bias; 294 * bias[1] == y_bias; bias[2] == z_bias). Bias is subtracted from uncalibrated 300 * If bias delivery is supported, this event is generated by default when 302 * CHRE_SENSOR_TYPE_GEOMAGNETIC_FIELD, or if bias delivery is explicitly enabled 312 * field within 'readings', or by the 3D array 'bias' (bias[0] == x_bias; 313 * bias[1] == y_bias; bias[2] == z_bias). Bias is subtracted from uncalibrated [all …]
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