[GitHub] [incubator-tvm] masahi commented on a change in pull request #4400: implement conv3d op

[GitBox <gi...@apache.org>]

masahi commented on a change in pull request #4400: implement conv3d op
URL: https://github.com/apache/incubator-tvm/pull/4400#discussion_r353545341
 
 

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 File path: topi/python/topi/cuda/conv3d.py
 ##########
 @@ -0,0 +1,142 @@
+# Licensed to the Apache Software Foundation (ASF) under one
+# or more contributor license agreements.  See the NOTICE file
+# distributed with this work for additional information
+# regarding copyright ownership.  The ASF licenses this file
+# to you under the Apache License, Version 2.0 (the
+# "License"); you may not use this file except in compliance
+# with the License.  You may obtain a copy of the License at
+#
+#   http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing,
+# software distributed under the License is distributed on an
+# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+# KIND, either express or implied.  See the License for the
+# specific language governing permissions and limitations
+# under the License.
+# pylint: disable=invalid-name
+"""Compute definition for conv3d with cuda backend"""
+import tvm
+from tvm import autotvm
+from tvm.contrib import cudnn
+
+from .. import nn, generic
+from ..util import get_const_tuple, traverse_inline
+
+from .conv3d_direct import schedule_direct_3d_cuda
+
+
+@autotvm.register_topi_compute(nn.conv3d, ['cuda', 'gpu'], ['direct'])
+def conv3d_cuda(cfg, data, kernel, strides, padding, dilation, layout='NCDHW', out_dtype='float32'):
+    """Conv3D operator for cuda backend.
+
+    Parameters
+    ----------
+    cfg: ConfigEntity
+        The config for this template
+
+    data : tvm.Tensor
+        5-D with shape [batch, in_channel, in_depth, in_height, in_width]
+
+    kernel : tvm.Tensor
+        5-D with shape [num_filter, in_channel, filter_depth, filter_height, filter_width]
+
+    strides : int or a list/tuple of three ints
+        stride size, or [stride_depth, stride_height, stride_width]
+
+    padding : int or a list/tuple of three ints
+        padding size, or [pad_depth, pad_height, pad_width]
+
+    dilation: int or a list/tuple of three ints
+        dilation size, or [dilation_depth, dilation_height, dilation_width]
+
+    layout : str
+        layout of data
+
+    out_dtype: str
+        The output type. This is used for mixed precision.
+
+    Returns
+    -------
+    output : tvm.Tensor
+        5-D with shape [batch, out_channel, out_depth, out_height, out_width]
+    """
+    target = tvm.target.current_target()
+
+    if "cudnn" in target.libs:
+        if layout == 'NCDHW':
+            tensor_format = 0 # CUDNN_TENSOR_NCHW
+            N, _, D, H, W = get_const_tuple(data.shape)
+        elif layout == 'NDHWC':
+            tensor_format = 1 # CUDNN_TENSOR_NHWC
+            N, D, H, W, _ = get_const_tuple(data.shape)
+        else:
+            raise ValueError("Unsupported layout %s in cudnn" % layout)
+        CO, CI, KD, KH, KW = get_const_tuple(kernel.shape)
+
+        # handle dilation
+        stride_d, stride_h, stride_w = (strides, strides, strides) if isinstance(strides, int) \
+            else strides
+        pad_d, pad_h, pad_w = (padding, padding, padding) if isinstance(padding, int) else padding
+        dilation_d, dilation_h, dilation_w = (dilation, dilation, dilation) if \
+            isinstance(dilation, int) else dilation
+
+        OD = (D + 2 * pad_d - KD) // stride_d + 1
+        OH = (H + 2 * pad_h - KH) // stride_h + 1
+        OW = (W + 2 * pad_w - KW) // stride_w + 1
+        cfg.add_flop(2 * N * OD * OH * OW * CO * CI * ((DH - 1) * dilation_d + 1) *\
+                    ((KH - 1) * dilation_h + 1) * ((KW - 1) * dilation_w + 1))
+
+        return cudnn.conv3d_forward(data,
 
 Review comment:
   this should be conv_forward

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