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Searched refs:out_dims (Results 1 – 25 of 46) sorted by relevance

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/dports/math/py-theano/Theano-1.0.5/theano/gpuarray/c_code/
H A Ddnn_sptf_sampler.c68 size_t out_dims[4]; in APPLY_SPECIFIC() local
96 out_dims[0] = (size_t) PyGpuArray_DIM(input, 0); // num_images in APPLY_SPECIFIC()
97 out_dims[1] = (size_t) PyGpuArray_DIM(input, 1); // num_channels in APPLY_SPECIFIC()
98 out_dims[2] = (size_t) PyGpuArray_DIM(grid, 1); // grid height in APPLY_SPECIFIC()
99 out_dims[3] = (size_t) PyGpuArray_DIM(grid, 2); // grid width in APPLY_SPECIFIC()
101 desc_dims[0] = (int) out_dims[0]; in APPLY_SPECIFIC()
102 desc_dims[1] = (int) out_dims[1]; in APPLY_SPECIFIC()
103 desc_dims[2] = (int) out_dims[2]; in APPLY_SPECIFIC()
104 desc_dims[3] = (int) out_dims[3]; in APPLY_SPECIFIC()
106 if ( out_dims[0] == 0 || out_dims[1] == 0 || out_dims[2] == 0 || out_dims[3] == 0 ) in APPLY_SPECIFIC()
[all …]
H A Ddnn_sptf_grid.c28 PyArrayObject * out_dims, in APPLY_SPECIFIC()
56 if ( PyArray_NDIM( out_dims ) != 1 || PyArray_SIZE( out_dims ) != 4 ) in APPLY_SPECIFIC()
64 num_images = (int) *( (npy_int64 *) PyArray_GETPTR1( out_dims, 0 ) ); in APPLY_SPECIFIC()
65 num_channels = (int) *( (npy_int64 *) PyArray_GETPTR1( out_dims, 1 ) ); in APPLY_SPECIFIC()
66 height = (int) *( (npy_int64 *) PyArray_GETPTR1( out_dims, 2 ) ); in APPLY_SPECIFIC()
67 width = (int) *( (npy_int64 *) PyArray_GETPTR1( out_dims, 3 ) ); in APPLY_SPECIFIC()
H A Ddnn_sptf_gi.c84 int out_dims[4]; in APPLY_SPECIFIC() local
131 out_dims[0] = (int) PyGpuArray_DIM(input, 0); // num_images in APPLY_SPECIFIC()
132 out_dims[1] = (int) PyGpuArray_DIM(input, 1); // num_channels in APPLY_SPECIFIC()
133 out_dims[2] = (int) PyGpuArray_DIM(grid, 1); // grid height in APPLY_SPECIFIC()
134 out_dims[3] = (int) PyGpuArray_DIM(grid, 2); // grid width in APPLY_SPECIFIC()
139 dt, 4, out_dims ); in APPLY_SPECIFIC()
/dports/science/py-chainer/chainer-7.8.0/chainerx_cc/chainerx/native/
H A Dim2col.cc35 const Dims& out_dims, in Im2ColImpl() argument
42 CHAINERX_ASSERT(kKernelNdim == static_cast<int8_t>(out_dims.size())); in Im2ColImpl()
47 Indexer<kKernelNdim> out_dims_indexer{Shape{out_dims.begin(), out_dims.end()}}; in Im2ColImpl()
104 Dims out_dims; // Number of patches along each axis in Im2Col() local
107 CHAINERX_ASSERT(out_dims.back() > 0); in Im2Col()
109 CHAINERX_ASSERT(ndim == static_cast<int8_t>(out_dims.size())); in Im2Col()
116 std::copy(out_dims.begin(), out_dims.end(), std::back_inserter(out_shape)); in Im2Col()
128 … Im2ColImpl<T, 0>(padded_x, out, kernel_size, stride, out_dims, batch_channel_indexer); in Im2Col()
131 … Im2ColImpl<T, 1>(padded_x, out, kernel_size, stride, out_dims, batch_channel_indexer); in Im2Col()
134 … Im2ColImpl<T, 2>(padded_x, out, kernel_size, stride, out_dims, batch_channel_indexer); in Im2Col()
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/dports/math/py-jax/jax-0.2.9/jax/interpreters/
H A Dbatching.py60 yield out_vals, out_dims
66 out_dims = out_dims_thunk()
67 for od, od_dest in zip(out_dims, out_dim_dests):
80 fun, out_dims = batch_subtrace(fun)
81 return _batch_fun2(fun, in_dims), out_dims
237 fst, out_dims = lu.merge_linear_aux(out_dims1, out_dims2)
239 assert out_dims == out_dims[:len(out_dims) // 2] * 2
240 out_dims = out_dims[:len(out_dims) // 2]
262 out_dims = out_dims[-len(out_vals) % len(out_dims):]
443 for d, inst in zip(out_dims, instantiate)]
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/dports/science/mpb/mpb-1.11.1/utils/
H A Dmpb-data.c304 out_dims[i] = 1; in handle_dataset()
306 N *= (out_dims[i] = MAX2(out_dims[i], 1)); in handle_dataset()
309 out_dims2[0] = out_dims[1]; in handle_dataset()
310 out_dims2[1] = out_dims[0]; in handle_dataset()
311 out_dims2[2] = out_dims[2]; in handle_dataset()
314 out_dims2[0] = out_dims[0]; in handle_dataset()
315 out_dims2[1] = out_dims[1]; in handle_dataset()
316 out_dims2[2] = out_dims[2]; in handle_dataset()
449 out_dims[i] = 1; in handle_cvector_dataset()
451 N *= (out_dims[i] = MAX2(out_dims[i], 1)); in handle_cvector_dataset()
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/dports/math/ideep/ideep-2.0.0-119-gb57539e/python/ideep4py/
H A D__init__.py291 def convolution2DParam(out_dims, dy, dx, sy, sx, ph, pw, pd, pr): argument
293 cp.out_dims = intVector()
294 for d in out_dims:
295 cp.out_dims.push_back(d)
303 def pooling2DParam(out_dims, kh, kw, sy, sx, ph, pw, pd, pr, algo): argument
305 pp.out_dims = intVector()
306 for d in out_dims:
307 pp.out_dims.push_back(d)
/dports/math/ideep/ideep-2.0.0-119-gb57539e/python/ideep4py/py/primitives/
H A Dconv_py.h52 *(bias->get()), cp->out_dims, dst, in Forward()
59 *(src->get()), *(weights->get()), cp->out_dims, dst, in Forward()
76 *(src->get()), *(grady->get()), cp->out_dims, gW, in BackwardWeights()
93 *(src->get()), *(grady->get()), cp->out_dims, gW, gb, in BackwardWeightsBias()
112 *(grady->get()), *(weights->get()), cp->out_dims, gx, in BackwardData()
H A Dparam.h31 std::vector<int> out_dims; member
39 std::vector<int> out_dims; member
H A Dparam.i27 std::vector<int> out_dims; member
36 std::vector<int> out_dims; member
H A Dpooling_py.h49 *(src->get()), pp->out_dims, dst, in Forward()
95 src.init({pp->out_dims, grady->get()->get_data_type(), in Backward()
96 engine::default_format(pp->out_dims.size())}, nullptr); in Backward()
/dports/misc/mxnet/incubator-mxnet-1.9.0/3rdparty/tvm/src/relay/transforms/
H A Dcombine_parallel_dense.cc184 auto out_dims = tir::as_const_int(out_shape[out_shape.size() - 1]); in UpdateGroupOutput() local
185 CHECK(out_dims != nullptr); in UpdateGroupOutput()
195 end.push_back(*out_dims); in UpdateGroupOutput()
197 index += *out_dims; in UpdateGroupOutput()
205 int64_t out_dims = 0; in TransformWeight() local
210 out_dims += *tir::as_const_int(weight->type_as<TensorTypeNode>()->shape[0]); in TransformWeight()
213 tir::make_const(DataType::Int(32), out_dims)); in TransformWeight()
/dports/science/py-chainer-chemistry/chainer-chemistry-0.7.1/chainer_chemistry/models/
H A Drsgcn.py45 out_dims = [hidden_channels for _ in range(n_update_layers)]
46 out_dims[n_update_layers - 1] = out_dim
52 *[RSGCNUpdate(in_dims[i], out_dims[i])
57 out_dims[i]) for i in range(n_update_layers)])
/dports/science/py-chainer/chainer-7.8.0/chainerx_cc/chainerx/cuda/
H A Dcuda_conv_test.cc153 Shape out_dims{5, 3}; in TEST() local
155 std::copy(out_dims.begin(), out_dims.end(), std::back_inserter(out_shape)); in TEST()
169 Shape out_dims{9, 5}; in TEST() local
171 std::copy(out_dims.begin(), out_dims.end(), std::back_inserter(out_shape)); in TEST()
/dports/math/py-matplotlib/matplotlib-3.4.3/src/
H A D_image_wrapper.cpp65 npy_intp out_dims[3]; in _get_transform_mesh() local
67 out_dims[0] = dims[0] * dims[1]; in _get_transform_mesh()
68 out_dims[1] = 2; in _get_transform_mesh()
75 numpy::array_view<double, 2> input_mesh(out_dims); in _get_transform_mesh()
/dports/math/py-matplotlib2/matplotlib-2.2.4/src/
H A D_image_wrapper.cpp69 npy_intp out_dims[3]; in _get_transform_mesh() local
71 out_dims[0] = dims[0] * dims[1]; in _get_transform_mesh()
72 out_dims[1] = 2; in _get_transform_mesh()
80 numpy::array_view<double, 2> input_mesh(out_dims); in _get_transform_mesh()
/dports/devel/py-qutip/qutip-4.6.2/qutip/
H A Dsuperop_reps.py336 out_dims, in_dims = q_oper.dims
337 out_left, out_right = out_dims
371 out_dims, in_dims = q_oper.dims
372 out_left, out_right = out_dims
/dports/misc/py-mxnet/incubator-mxnet-1.9.0/src/operator/subgraph/mkldnn/
H A Dmkldnn_fc.cc193 mkldnn::memory::dims out_dims(2); in Forward() local
195 out_dims[0] = static_cast<int>(oshape[0]); in Forward()
196 out_dims[1] = static_cast<int>(oshape[1]); in Forward()
199 out_dims[0] = static_cast<int>(oshape.ProdShape(0, oshape.ndim()-1)); in Forward()
200 out_dims[1] = static_cast<int>(oshape[oshape.ndim()-1]); in Forward()
202 out_dims[0] = static_cast<int>(static_cast<int>(oshape[0])); in Forward()
203 out_dims[1] = static_cast<int>(oshape.ProdShape(1, oshape.ndim())); in Forward()
206 mkldnn::memory::desc out_md = mkldnn::memory::desc(out_dims, get_mkldnn_type(output.dtype()), in Forward()
/dports/misc/mxnet/incubator-mxnet-1.9.0/src/operator/subgraph/mkldnn/
H A Dmkldnn_fc.cc193 mkldnn::memory::dims out_dims(2); in Forward() local
195 out_dims[0] = static_cast<int>(oshape[0]); in Forward()
196 out_dims[1] = static_cast<int>(oshape[1]); in Forward()
199 out_dims[0] = static_cast<int>(oshape.ProdShape(0, oshape.ndim()-1)); in Forward()
200 out_dims[1] = static_cast<int>(oshape[oshape.ndim()-1]); in Forward()
202 out_dims[0] = static_cast<int>(static_cast<int>(oshape[0])); in Forward()
203 out_dims[1] = static_cast<int>(oshape.ProdShape(1, oshape.ndim())); in Forward()
206 mkldnn::memory::desc out_md = mkldnn::memory::desc(out_dims, get_mkldnn_type(output.dtype()), in Forward()
/dports/science/hdf5-18/hdf5-1.8.21/test/
H A Dtsohm.c3237 hsize_t out_dims[2]; in test_sohm_extend_dset_helper() local
3357 VERIFY(out_dims[x], dims2[x], "H5Sget_simple_extent_dims"); in test_sohm_extend_dset_helper()
3364 VERIFY(out_dims[x], dims1[x], "H5Sget_simple_extent_dims"); in test_sohm_extend_dset_helper()
3371 VERIFY(out_dims[x], dims1[x], "H5Sget_simple_extent_dims"); in test_sohm_extend_dset_helper()
3419 VERIFY(out_dims[x], dims2[x], "H5Sget_simple_extent_dims"); in test_sohm_extend_dset_helper()
3426 VERIFY(out_dims[x], dims2[x], "H5Sget_simple_extent_dims"); in test_sohm_extend_dset_helper()
3433 VERIFY(out_dims[x], dims1[x], "H5Sget_simple_extent_dims"); in test_sohm_extend_dset_helper()
3481 VERIFY(out_dims[x], dims2[x], "H5Sget_simple_extent_dims"); in test_sohm_extend_dset_helper()
3488 VERIFY(out_dims[x], dims2[x], "H5Sget_simple_extent_dims"); in test_sohm_extend_dset_helper()
3495 VERIFY(out_dims[x], dims2[x], "H5Sget_simple_extent_dims"); in test_sohm_extend_dset_helper()
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/dports/misc/mxnet/incubator-mxnet-1.9.0/3rdparty/mkldnn/src/gpu/ocl/rnn/
H A Drnn_reorders.cpp103 const auto &out_dims = dst_mdw.padded_dims(); in init_kernel_ctx() local
111 (d < dst_mdw.ndims()) ? out_dims[d] : 1); in init_kernel_ctx()
/dports/math/onednn/oneDNN-2.5.1/src/gpu/ocl/rnn/
H A Drnn_reorders.cpp103 const auto &out_dims = dst_mdw.padded_dims(); in init_kernel_ctx() local
111 (d < dst_mdw.ndims()) ? out_dims[d] : 1); in init_kernel_ctx()
/dports/misc/py-mxnet/incubator-mxnet-1.9.0/src/operator/nn/mkldnn/
H A Dmkldnn_fully_connected.cc161 mkldnn::memory::dims out_dims{static_cast<int>(oshape.ProdShape(0, oshape.ndim()-1)), in MKLDNNFCFlattenData() local
163 *out_md = mkldnn::memory::desc(out_dims, get_mkldnn_type(out_data.dtype()), in MKLDNNFCFlattenData()
167 mkldnn::memory::dims out_dims{static_cast<int>(oshape[0]), in MKLDNNFCFlattenData() local
169 *out_md = mkldnn::memory::desc(out_dims, get_mkldnn_type(out_data.dtype()), in MKLDNNFCFlattenData()
/dports/misc/mxnet/incubator-mxnet-1.9.0/src/operator/nn/mkldnn/
H A Dmkldnn_fully_connected.cc161 mkldnn::memory::dims out_dims{static_cast<int>(oshape.ProdShape(0, oshape.ndim()-1)), in MKLDNNFCFlattenData() local
163 *out_md = mkldnn::memory::desc(out_dims, get_mkldnn_type(out_data.dtype()), in MKLDNNFCFlattenData()
167 mkldnn::memory::dims out_dims{static_cast<int>(oshape[0]), in MKLDNNFCFlattenData() local
169 *out_md = mkldnn::memory::desc(out_dims, get_mkldnn_type(out_data.dtype()), in MKLDNNFCFlattenData()
/dports/science/minc2/minc-release-2.2.00/progs/mincresample/
H A Dmincresample.c1291 int ndims, in_dims[MAX_VAR_DIMS], out_dims[MAX_VAR_DIMS]; in create_output_file() local
1384 out_dims[out_index] = ncdimid(out_file->mincid, dimname); in create_output_file()
1386 dim_exists = (out_dims[out_index] != MI_ERROR); in create_output_file()
1400 (void) ncdimrename(out_file->mincid, out_dims[out_index], string); in create_output_file()
1402 out_dims[out_index] = ncdimdef(out_file->mincid, dimname, in create_output_file()
1406 out_dims[out_index] = ncdimdef(out_file->mincid, dimname, in create_output_file()
1434 ncdiminq(out_file->mincid, out_dims[ndims-1], dimname, NULL); in create_output_file()
1444 out_maxmin_dims[nmaxmin_dims] = out_dims[idim]; in create_output_file()
1518 ndims, out_dims); in create_output_file()

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