| /dports/misc/mxnet/incubator-mxnet-1.9.0/3rdparty/tvm/python/tvm/topi/nn/ |
| H A D | pooling.py | 60 data, kernel, stride, padding, pool_type, ceil_mode=False, layout="NCHW", count_include_pad=True argument
126 ceil_mode=False, argument
238 data, kernel, stride, padding, pool_type, ceil_mode=False, layout="NCW", count_include_pad=True argument
311 ceil_mode=False, argument
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| /dports/misc/py-onnx-tf/onnx-tf-1.6.0/onnx_tf/common/ |
| H A D | pooling_helper.py | 79 padding, ceil_mode=False): argument
112 def _pooling_output_shape(input_size, ksize, stride, dilation, pad, ceil_mode): argument
122 padding=None, ceil_mode=False, pooling_type="MAX", argument
|
| /dports/misc/mxnet/incubator-mxnet-1.9.0/3rdparty/tvm/src/relay/op/nn/ |
| H A D | pooling.h | 37 Array<IndexExpr> padding, String layout, bool ceil_mode, String op_name) { in MakeMaxPool()
50 Array<IndexExpr> padding, String layout, bool ceil_mode, in MakeAvgPool()
|
| H A D | pooling.cc | 138 auto ceil_mode = param->ceil_mode; in Pool2DCompute() local
173 Array<IndexExpr> padding, String layout, bool ceil_mode) { in __anon3b839d080102()
211 bool count_include_pad) { in __anon3b839d080202()
689 auto ceil_mode = param->ceil_mode; in Pool2DGradCompute() local
729 bool ceil_mode) { in MakeMaxPool2DGrad()
775 bool ceil_mode, bool count_include_pad) { in MakeAvgPool2DGrad()
880 auto ceil_mode = param->ceil_mode; in Pool1DCompute() local
909 Array<IndexExpr> padding, String layout, bool ceil_mode) { in __anon3b839d080302()
945 bool count_include_pad) { in __anon3b839d080402()
1058 auto ceil_mode = param->ceil_mode; in Pool3DCompute() local
[all …]
|
| /dports/misc/mxnet/incubator-mxnet-1.9.0/3rdparty/tvm/tests/python/topi/python/ |
| H A D | test_topi_pooling.py | 49 def verify_pool(n, ic, ih, kh, sh, padding, pool_type, ceil_mode, count_include_pad=True): argument
126 n, ic, ih, kh, sh, padding, pool_type, ceil_mode, count_include_pad=True, add_relu=False argument
341 n, ic, ih, kh, sh, padding, pool_type, ceil_mode, count_include_pad=True, layout="NCDHW" argument
405 n, ic, iw, kw, sw, padding, pool_type, ceil_mode, count_include_pad=True, layout="NCW" argument
|
| /dports/misc/tvm/incubator-tvm-0.6.1/topi/python/topi/nn/ |
| H A D | pooling.py | 66 ceil_mode=False, argument
123 ceil_mode=False, argument
|
| /dports/misc/py-tvm/incubator-tvm-0.6.1/topi/python/topi/nn/ |
| H A D | pooling.py | 66 ceil_mode=False, argument
123 ceil_mode=False, argument
|
| /dports/misc/py-tvm/incubator-tvm-0.6.1/src/relay/op/nn/ |
| H A D | pooling.cc | 136 bool ceil_mode) { in MakeMaxPool2D()
158 auto ceil_mode = param->ceil_mode; in Pool2DCompute() local
235 bool ceil_mode, in MakeAvgPool2D()
590 auto ceil_mode = param->ceil_mode; in Pool2DGradCompute() local
629 Array<IndexExpr> strides, Array<IndexExpr> padding, std::string layout, bool ceil_mode) { in MakeMaxPool2DGrad()
676 Array<IndexExpr> strides, Array<IndexExpr> padding, std::string layout, bool ceil_mode, in MakeAvgPool2DGrad()
|
| /dports/misc/tvm/incubator-tvm-0.6.1/src/relay/op/nn/ |
| H A D | pooling.cc | 136 bool ceil_mode) { in MakeMaxPool2D()
158 auto ceil_mode = param->ceil_mode; in Pool2DCompute() local
235 bool ceil_mode, in MakeAvgPool2D()
590 auto ceil_mode = param->ceil_mode; in Pool2DGradCompute() local
629 Array<IndexExpr> strides, Array<IndexExpr> padding, std::string layout, bool ceil_mode) { in MakeMaxPool2DGrad()
676 Array<IndexExpr> strides, Array<IndexExpr> padding, std::string layout, bool ceil_mode, in MakeAvgPool2DGrad()
|
| /dports/misc/tvm/incubator-tvm-0.6.1/tests/python/relay/ |
| H A D | test_op_grad_level2.py | 27 def verify_max_pool2d_grad(x_shape, pool_size, strides, padding, ceil_mode): argument
55 def verify_avg_pool2d_grad(x_shape, pool_size, strides, padding, ceil_mode, count_include_pad): argument
|
| /dports/misc/mxnet/incubator-mxnet-1.9.0/3rdparty/tvm/tests/python/relay/ |
| H A D | test_op_grad_level2.py | 29 def verify_max_pool2d_grad(x_shape, pool_size, strides, padding, ceil_mode): argument
69 def verify_avg_pool2d_grad(x_shape, pool_size, strides, padding, ceil_mode, count_include_pad): argument
|
| /dports/misc/py-tvm/incubator-tvm-0.6.1/tests/python/relay/ |
| H A D | test_op_grad_level2.py | 27 def verify_max_pool2d_grad(x_shape, pool_size, strides, padding, ceil_mode): argument
55 def verify_avg_pool2d_grad(x_shape, pool_size, strides, padding, ceil_mode, count_include_pad): argument
|
| /dports/misc/mxnet/incubator-mxnet-1.9.0/3rdparty/tvm/tests/python/contrib/test_arm_compute_lib/ |
| H A D | test_pooling.py | 42 shape, dtype, typef, sizes, strides, padding, ceil_mode, count_include_pad, var_names argument
109 shape, dtype, typef, sizes, strides, padding, ceil_mode, count_include_pad argument
|
| /dports/misc/tvm/incubator-tvm-0.6.1/topi/python/topi/testing/ |
| H A D | pool_grad_python.py | 27 ceil_mode, argument
|
| /dports/misc/mxnet/incubator-mxnet-1.9.0/3rdparty/tvm/python/tvm/topi/testing/ |
| H A D | pool_grad_python.py | 23 a_np, out_grad_np, pool_size, strides, padding, pool_type, ceil_mode, count_include_pad=True argument
|
| H A D | pool1d_python.py | 31 ceil_mode=False, argument
|
| H A D | pool3d_python.py | 32 ceil_mode=False, argument
|
| /dports/misc/py-tvm/incubator-tvm-0.6.1/topi/python/topi/testing/ |
| H A D | pool_grad_python.py | 27 ceil_mode, argument
|
| /dports/misc/tvm/incubator-tvm-0.6.1/topi/tests/python/ |
| H A D | test_topi_pooling.py | 27 def verify_pool(n, ic, ih, kh, sh, padding, pool_type, ceil_mode, count_include_pad=True): argument
89 def verify_pool_grad(n, ic, ih, kh, sh, padding, pool_type, ceil_mode, count_include_pad=True, argument
|
| /dports/misc/py-tvm/incubator-tvm-0.6.1/topi/tests/python/ |
| H A D | test_topi_pooling.py | 27 def verify_pool(n, ic, ih, kh, sh, padding, pool_type, ceil_mode, count_include_pad=True): argument
89 def verify_pool_grad(n, ic, ih, kh, sh, padding, pool_type, ceil_mode, count_include_pad=True, argument
|
| /dports/misc/mnn/MNN-1.2.0/tools/converter/source/torch/ |
| H A D | PoolTorch.cpp | 44 const auto ceil_mode = getValue<bool>(inputs[5]); in run() local
|
| /dports/misc/mxnet/incubator-mxnet-1.9.0/python/mxnet/gluon/nn/ |
| H A D | conv_layers.py | 708 def __init__(self, pool_size, strides, padding, ceil_mode, global_pool, argument
776 ceil_mode=False, **kwargs): argument
825 ceil_mode=False, **kwargs): argument
876 ceil_mode=False, layout='NCDHW', **kwargs): argument
923 ceil_mode=False, count_include_pad=True, **kwargs): argument
974 ceil_mode=False, layout='NCHW', count_include_pad=True, **kwargs): argument
1027 ceil_mode=False, layout='NCDHW', count_include_pad=True, **kwargs): argument
|
| /dports/misc/py-mxnet/incubator-mxnet-1.9.0/python/mxnet/gluon/nn/ |
| H A D | conv_layers.py | 708 def __init__(self, pool_size, strides, padding, ceil_mode, global_pool, argument
776 ceil_mode=False, **kwargs): argument
825 ceil_mode=False, **kwargs): argument
876 ceil_mode=False, layout='NCDHW', **kwargs): argument
923 ceil_mode=False, count_include_pad=True, **kwargs): argument
974 ceil_mode=False, layout='NCHW', count_include_pad=True, **kwargs): argument
1027 ceil_mode=False, layout='NCDHW', count_include_pad=True, **kwargs): argument
|
| /dports/misc/tvm/incubator-tvm-0.6.1/tests/webgl/ |
| H A D | test_local_topi_pooling.py | 27 def verify_pool(n, ic, ih, kh, sh, padding, pool_type, ceil_mode): argument
|
| /dports/misc/py-tvm/incubator-tvm-0.6.1/tests/webgl/ |
| H A D | test_local_topi_pooling.py | 27 def verify_pool(n, ic, ih, kh, sh, padding, pool_type, ceil_mode): argument
|