Searched refs:mul_result (Results 1 – 6 of 6) sorted by relevance
| /third_party/mindspore/mindspore/ccsrc/backend/kernel_compiler/cpu/nnacl/int8/ |
| D | mul_int8.c | 202 int32_t mul_result = RoundingDivideByPOT( in FastMul() local
207 mul_result += quant_arg->out_quant_arg_.zp_; in FastMul()
208 …mul_result = mul_result < quant_arg->output_activation_max_ ? mul_result : quant_arg->output_activ… in FastMul()
209 …mul_result = mul_result > quant_arg->output_activation_min_ ? mul_result : quant_arg->output_activ… in FastMul()
210 output_data[0] = (int8_t)mul_result; in FastMul()
227 int32_t mul_result = RoundingDivideByPOT( in Mul() local
232 mul_result += quant_arg->out_quant_arg_.zp_; in Mul()
233 …mul_result = mul_result < quant_arg->output_activation_max_ ? mul_result : quant_arg->output_activ… in Mul()
234 …mul_result = mul_result > quant_arg->output_activation_min_ ? mul_result : quant_arg->output_activ… in Mul()
235 output_data[index] = (int8_t)mul_result; in Mul()
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| D | scale_int8.c | 89 int32_t mul_result = RoundingDivideByPOT( in DoScaleInt8() local
94 mul_result += scale_param->output_zp_; in DoScaleInt8()
96 if (mul_result > scale_param->output_activation_max_) { in DoScaleInt8()
98 } else if (mul_result < scale_param->output_activation_min_) { in DoScaleInt8()
101 out_data[index] = (int8_t)mul_result; in DoScaleInt8()
143 int32_t mul_result = RoundingDivideByPOT( in DoScaleWithBiasInt8() local
153 mul_result += bias + scale_param->output_zp_; in DoScaleWithBiasInt8()
155 if (mul_result > scale_param->output_activation_max_) { in DoScaleWithBiasInt8()
157 } else if (mul_result < scale_param->output_activation_min_) { in DoScaleWithBiasInt8()
160 out_data[index] = (int8_t)mul_result; in DoScaleWithBiasInt8()
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| /third_party/mindspore/mindspore/_extends/graph_kernel/expanders/ |
| D | logsoftmax_grad.py | 33 mul_result = graph_builder.emit('Mul', [softmax, dy_sum])
34 result = graph_builder.emit('Sub', [input_dy, mul_result])
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| /third_party/mindspore/mindspore/ops/composite/ |
| D | math_ops.py | 300 mul_result = matmul_op(x1_reshaped, x2_reshaped)
301 final_result = reshape_op(mul_result, output_shape)
416 mul_result = matmul_op(x1_reshape, x2_reshape)
417 return reshape_op(mul_result, x1_shape[:-1] + x2_shape[:-2] + x2_shape[-1:])
640 mul_result = batch_matmul_op(x1_reshaped, x2_reshaped)
642 final_result = F.reshape(mul_result, output_shape)
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| /third_party/mesa3d/src/compiler/spirv/ |
| D | vtn_alu.c | 1018 nir_ssa_def *const mul_result = nir_imul(&b->nb, src0, src1); in vtn_handle_integer_dot() local
1020 dest = (i == 0) ? mul_result : nir_iadd(&b->nb, dest, mul_result); in vtn_handle_integer_dot()
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| /third_party/mesa3d/src/compiler/nir/ |
| D | nir_loop_analyze.c | 831 nir_const_value mul_result = in test_iterations() local
836 eval_const_binop(add_op, bit_size, mul_result, initial, execution_mode); in test_iterations()
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