| /third_party/mindspore/mindspore/ccsrc/backend/kernel_compiler/gpu/cuda_impl/ |
| D | instance_norm_impl.cu | 63 … float *dgamma, float *dbeta, const float *ws_dgamma, const float *ws_dbeta) { in ComputeMeanKernel() argument
77 dbeta[cur_local_index] = tmp; in ComputeMeanKernel()
83 float *dgamma, float *dbeta, const float *ws_dgamma, const float *ws_dbeta, in ComputeMean() argument
87 thread_num, N, C, dgamma, dbeta, ws_dgamma, ws_dbeta); in ComputeMean()
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| D | instance_norm_impl.cuh | 25 void ComputeMean(const size_t N, const size_t C, float *dgamma, float *dbeta, const float *ws_dgamm…
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| /third_party/mindspore/mindspore/ccsrc/backend/kernel_compiler/cpu/nnacl/fp32_grad/ |
| D | layernorm_grad.c | 31 float dbeta = 0.0f; in LayerNormGrad() local
35 dbeta += dy[j]; in LayerNormGrad()
38 db[i] = dbeta; in LayerNormGrad()
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| /third_party/mindspore/mindspore/_extends/graph_kernel/expanders/ |
| D | batchnorm_grad.py | 51 …dbeta = graph_builder.emit('ReduceSum', [input_dy], attrs={'reduce_axis': reduce_axis, 'keep_dims'…
80 tmp_b = graph_builder.emit('Mul', [num_rec_v, dbeta])
103 dbeta.data_format = self.outputs[2]['format']
105 return dx, dgamma, dbeta
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| /third_party/mindspore/mindspore/ccsrc/backend/kernel_compiler/cpu/nnacl/fp16_grad/ |
| D | layernorm_grad.c | 28 float dbeta = 0.0f; in LayerNormFp16Grad() local
32 dbeta += dy[j]; in LayerNormFp16Grad()
35 db[i] = (float16_t)dbeta; in LayerNormFp16Grad()
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| /third_party/mindspore/mindspore/ccsrc/backend/kernel_compiler/cpu/ |
| D | layer_norm_grad_cpu_kernel.cc | 99 T dbeta = (T)0.0; in LaunchKernel() local
103 dbeta += dy[j]; in LaunchKernel()
106 db[param_index] = dbeta; in LaunchKernel()
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| /third_party/mindspore/mindspore/ccsrc/backend/kernel_compiler/gpu/nn/ |
| D | instance_norm_grad_gpu_kernel.h | 73 auto dbeta = GetDeviceAddress<float>(outputs, 2); in Launch() local
99 … ComputeMean(N, C, dgamma, dbeta, ws_dgamma, ws_dbeta, reinterpret_cast<cudaStream_t>(stream_ptr)); in Launch()
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| /third_party/boost/boost/geometry/formulas/ |
| D | sjoberg_intersection.hpp | 898 CT const dbeta = (lon1_minus_lon2 + lon1_diff - lon2_diff) / dbeta_denom; in newton_method() local
900 CT const abs_dbeta = math::abs(dbeta); in newton_method()
909 if (math::equals(dbeta, c0)) in newton_method()
916 beta = beta - dbeta; in newton_method()
1111 CT const dbeta = beta_new - beta; in converge_07_update() local
1115 return math::equals(dbeta, c0); in converge_07_update()
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| /third_party/mindspore/tests/vm_impl/ |
| D | vm_me.py | 139 dbeta = np.sum(dout, axis=0)
140 return dx, dgamma, dbeta
149 dx, dgamma, dbeta = _batch_norm_grad(dy, x, scale, save_mean, save_inv_variance)
152 return dx, dgamma, dbeta
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| /third_party/boost/libs/math/doc/distributions/ |
| D | nc_f.qbk | 94 package] and its pbeta and dbeta functions.
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| /third_party/mindspore/mindspore/ops/_grad/ |
| D | grad_nn_ops.py | 696 dbeta = out[2]
697 return dx, dgamma, dbeta, zeros_like(mean), zeros_like(variance)
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| /third_party/boost/libs/math/reporting/performance/ |
| D | test_distributions.cpp | 622 …beta.run_timed_tests([](const std::vector<double>& v, double x) { return dbeta(x, v[0], v[1], 0);… in main()
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