Home
last modified time | relevance | path

Searched refs:ksize_ (Results 1 – 9 of 9) sorted by relevance

/external/tensorflow/tensorflow/core/kernels/
Davgpooling_op.cc62 OP_REQUIRES_OK(context, context->GetAttr("ksize", &ksize_)); in AvgPoolingOp()
63 OP_REQUIRES(context, ksize_.size() == 4, in AvgPoolingOp()
71 OP_REQUIRES(context, ksize_[0] == 1 && stride_[0] == 1, in AvgPoolingOp()
78 PoolParameters params{context, ksize_, stride_, in Compute()
99 std::vector<int32> ksize_; member in tensorflow::AvgPoolingOp
125 OP_REQUIRES_OK(context, context->GetAttr("ksize", &ksize_)); in AvgPoolingOp()
126 OP_REQUIRES(context, ksize_.size() == 4, in AvgPoolingOp()
134 const int32 ksize_n = GetTensorDim(ksize_, data_format_, 'N'); in AvgPoolingOp()
143 PoolParameters params{context, ksize_, stride_, in Compute()
159 DnnPoolingOp<T>::Compute(context, se::dnn::PoolingMode::kAverage, ksize_, in Compute()
[all …]
Dmaxpooling_op.cc226 OP_REQUIRES_OK(context, context->GetAttr("ksize", &ksize_)); in MaxPoolingGradOp()
227 OP_REQUIRES(context, ksize_.size() == 4, in MaxPoolingGradOp()
234 OP_REQUIRES(context, ksize_[0] == 1 && stride_[0] == 1, in MaxPoolingGradOp()
238 context, ksize_[3] == 1 && stride_[3] == 1, in MaxPoolingGradOp()
270 std::vector<int32> ksize = ksize_; in Compute()
314 std::vector<int32> ksize_; member in tensorflow::MaxPoolingGradOp
357 OP_REQUIRES_OK(context, context->GetAttr("ksize", &ksize_)); in MaxPoolingGradOp()
358 OP_REQUIRES(context, ksize_.size() == 4, in MaxPoolingGradOp()
365 const int32 ksize_n = GetTensorDim(ksize_, data_format_, 'N'); in MaxPoolingGradOp()
394 std::vector<int32> ksize = ksize_; in Compute()
[all …]
Dpooling_ops_3d.cc145 OP_REQUIRES_OK(context, context->GetAttr("ksize", &ksize_)); in Pooling3DOp()
146 OP_REQUIRES(context, ksize_.size() == 5, in Pooling3DOp()
155 (GetTensorDim(ksize_, data_format_, 'N') == 1 && in Pooling3DOp()
160 (GetTensorDim(ksize_, data_format_, 'C') == 1 && in Pooling3DOp()
179 std::array<int64, 3> window{{GetTensorDim(ksize_, data_format_, '2'), in Compute()
180 GetTensorDim(ksize_, data_format_, '1'), in Compute()
181 GetTensorDim(ksize_, data_format_, '0')}}; in Compute()
200 std::vector<int32> ksize_; member in tensorflow::Pooling3DOp
318 OP_REQUIRES_OK(context, context->GetAttr("ksize", &ksize_)); in MaxPooling3dGradOp()
319 OP_REQUIRES(context, ksize_.size() == 5, in MaxPooling3dGradOp()
[all …]
Dquantized_pooling_ops.cc41 OP_REQUIRES_OK(context, context->GetAttr("ksize", &ksize_)); in QuantizedAvgPoolingOp()
42 OP_REQUIRES(context, ksize_.size() == 4, in QuantizedAvgPoolingOp()
50 OP_REQUIRES(context, ksize_[0] == 1 && stride_[0] == 1, in QuantizedAvgPoolingOp()
57 PoolParameters params{context, ksize_, stride_, in Compute()
103 std::vector<int32> ksize_; member in tensorflow::QuantizedAvgPoolingOp
Dmkl_avgpooling_op.cc54 OP_REQUIRES_OK(context, context->GetAttr("ksize", &ksize_)); in MklAvgPoolingOp()
55 OP_REQUIRES(context, ksize_.size() == 4, in MklAvgPoolingOp()
63 OP_REQUIRES(context, ksize_[0] == 1 && stride_[0] == 1, in MklAvgPoolingOp()
81 pool_params.Init(context, ksize_, stride_, padding_, data_format_, in Compute()
84 pool_params.Init(context, ksize_, stride_, padding_, data_format_, in Compute()
211 std::vector<int32> ksize_; member in tensorflow::MklAvgPoolingOp
229 OP_REQUIRES_OK(context, context->GetAttr("ksize", &ksize_)); in MklAvgPoolingGradOp()
230 OP_REQUIRES(context, ksize_.size() == 4, in MklAvgPoolingGradOp()
238 OP_REQUIRES(context, ksize_[0] == 1 && stride_[0] == 1, in MklAvgPoolingGradOp()
258 pool_params.Init(context, ksize_, stride_, padding_, data_format_, in Compute()
[all …]
Dmkl_maxpooling_op.cc55 OP_REQUIRES_OK(context, context->GetAttr("ksize", &ksize_)); in MklMaxPoolingOp()
56 OP_REQUIRES(context, ksize_.size() == 4, in MklMaxPoolingOp()
64 OP_REQUIRES(context, ksize_[0] == 1 && stride_[0] == 1, in MklMaxPoolingOp()
86 pool_params.Init(context, ksize_, stride_, padding_, data_format_, in Compute()
93 pool_params.Init(context, ksize_, stride_, padding_, data_format_, in Compute()
191 std::vector<int32> ksize_; member in tensorflow::MklMaxPoolingOp
214 OP_REQUIRES_OK(context, context->GetAttr("ksize", &ksize_)); in MklMaxPoolingGradOp()
215 OP_REQUIRES(context, ksize_.size() == 4, in MklMaxPoolingGradOp()
223 OP_REQUIRES(context, ksize_[0] == 1 && stride_[0] == 1, in MklMaxPoolingGradOp()
253 pool_params.Init(context, ksize_, stride_, padding_, data_format_, in Compute()
[all …]
Dmkl_pooling_ops_common.h460 OP_REQUIRES_OK(context, context->GetAttr("ksize", &this->ksize_)); in MklPoolingOpBase()
461 OP_REQUIRES(context, this->ksize_.size() == 4 || this->ksize_.size() == 5, in MklPoolingOpBase()
469 OP_REQUIRES(context, this->ksize_[0] == 1 && this->stride_[0] == 1, in MklPoolingOpBase()
472 bool is_pool2d = (this->ksize_.size() == 4); in MklPoolingOpBase()
492 if (this->ksize_.size() == 4) { in GetOutputDims()
513 pool_params->Init(context, this->ksize_, this->stride_, this->padding_, in InitMklPoolParameters()
516 pool_params->Init(context, this->ksize_, this->stride_, this->padding_, in InitMklPoolParameters()
588 std::vector<int32> ksize_; variable
617 (this->ksize_.size() == 4) in ConfigureInput()
625 if (this->ksize_.size() == 5) { in ConfigureInput()
[all …]
Dpooling_ops_common.h95 OP_REQUIRES_OK(context, context->GetAttr("ksize", &ksize_)); in MaxPoolingOp()
96 OP_REQUIRES(context, ksize_.size() == 4, in MaxPoolingOp()
104 OP_REQUIRES(context, ksize_[0] == 1 && stride_[0] == 1, in MaxPoolingOp()
111 PoolParameters params{context, ksize_, stride_, in Compute()
258 std::vector<int32> ksize_; variable
307 OP_REQUIRES_OK(context, context->GetAttr("ksize", &ksize_));
308 OP_REQUIRES(context, ksize_.size() == 4,
315 OP_REQUIRES(context, ksize_[0] == 1 && stride_[0] == 1,
325 std::vector<int32> ksize = ksize_;
505 std::vector<int32> ksize_;
/external/tensorflow/tensorflow/compiler/tf2xla/kernels/
Dpooling_ops.cc60 ksize_.push_back(ksize_int[i]); in PoolingOp()
77 return ksize_; in GetKernelSize()
125 std::vector<int64> ksize_; member in tensorflow::__anon05e5a9280111::PoolingOp
271 OP_REQUIRES_OK(ctx, ctx->GetAttr("ksize", &ksize_)); in MaxPoolGradOp()
289 OP_REQUIRES_OK(ctx, ctx->ConstantInputAsIntVector(3, &ksize_)); in Compile()
299 OP_REQUIRES(ctx, ksize_.size() == num_dims(), in Compile()
338 xla::SelectAndScatter(input, select, ksize_, stride_, xla_padding, in Compile()
346 std::vector<int64> ksize_; member in tensorflow::__anon05e5a9280111::MaxPoolGradOp
380 OP_REQUIRES_OK(ctx, ctx->GetAttr("ksize", &ksize_)); in AvgPoolGradOp()
381 OP_REQUIRES(ctx, ksize_.size() == num_dims(), in AvgPoolGradOp()
[all …]