masahi commented on a change in pull request #4418: [RUNTIME] Add cudnn conv3d URL: https://github.com/apache/incubator-tvm/pull/4418#discussion_r351923919
########## File path: topi/python/topi/testing/conv3d_ncdhw_python.py ########## @@ -0,0 +1,127 @@ +# 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, line-too-long, unused-variable, too-many-locals, too-many-branches +"""Convolution in python""" +import numpy as np +import scipy.signal + + +def _conv3d_ncdhw_python(a_np, w_np, stride, padding): + """Convolution operator in NCDHW layout. + + Parameters + ---------- + a_np : numpy.ndarray + 5-D with shape [batch, in_channel, in_depth, in_height, in_width] + + w_np : numpy.ndarray + 5-D with shape [num_filter, in_channel, filter_depth, filter_height, filter_width] + + stride : int or a list/tuple of three ints + Stride size, or [stride_depth, stride_height, stride_width] + + padding : int or str or a list/tuple of three ints + Padding size, or ['VALID', 'SAME'], or [pad_depth, pad_height, pad_width] + + Returns + ------- + b_np : np.ndarray + 5-D with shape [batch, out_channel, out_depth, out_height, out_width] + """ + batch, in_channel, in_depth, in_height, in_width = a_np.shape + num_filter, _, kernel_d, kernel_h, kernel_w = w_np.shape + if isinstance(stride, int): + stride_d = stride_h = stride_w = stride + else: + stride_d, stride_h, stride_w = stride + if isinstance(padding, int): + pad_d = pad_h = pad_w = padding * 2 + elif isinstance(padding, (list, tuple)): + pad_d, pad_h, pad_w = padding[0] * 2, padding[1] * 2, padding[2] * 2 + else: + pad_d = 0 if padding == 'VALID' else kernel_d - 1 + pad_h = 0 if padding == 'VALID' else kernel_h - 1 + pad_w = 0 if padding == 'VALID' else kernel_w - 1 + pad_front = int(np.ceil(float(pad_d) / 2)) + pad_back = pad_d - pad_front + pad_top = int(np.ceil(float(pad_h) / 2)) + pad_bottom = pad_h - pad_top + pad_left = int(np.ceil(float(pad_w) / 2)) + pad_right = pad_w - pad_left + # compute the output shape + out_channel = num_filter + out_depth = (in_depth - kernel_d + pad_d) // stride_d + 1 + out_height = (in_height - kernel_h + pad_h) // stride_h + 1 + out_width = (in_width - kernel_w + pad_w) // stride_w + 1 + b_np = np.zeros((batch, out_channel, out_depth, out_height, out_width)) + # computation + for n in range(batch): + for f in range(out_channel): + for c in range(in_channel): + if pad_d > 0 or pad_h > 0 or pad_w > 0: + apad = np.zeros((in_depth + pad_d, in_height + pad_h, in_width + pad_w)) + if pad_d == 0 and pad_h == 0: + apad[:, :, pad_left:-pad_right] = a_np[n, c] + elif pad_d == 0 and pad_w == 0: + apad[:, pad_top:-pad_bottom, :] = a_np[n, c] + elif pad_d == 0 and pad_h != 0 and pad_w != 0: + apad[:, pad_top:-pad_bottom, pad_left:-pad_right] = a_np[n, c] + elif pad_d != 0 and pad_h == 0: + apad[pad_front:-pad_back, :, pad_left:-pad_right] = a_np[n, c] + elif pad_d != 0 and pad_w == 0: + apad[pad_front:-pad_back, pad_top:-pad_bottom, :] = a_np[n, c] + elif pad_d != 0 and pad_h != 0 and pad_w != 0: + apad[pad_front:-pad_back, pad_top:-pad_bottom, pad_left:-pad_right] = a_np[n, c] + + else: + apad = a_np[n, c] + out = scipy.signal.convolve( + apad, np.flip(w_np[f, c]), mode='valid') + b_np[n, f] += out[::stride_d, ::stride_h, ::stride_w] + return b_np + + +def conv3d_ncdhw_python(a_np, w_np, stride, padding, groups=1): + """Convolution operator in NCHW layout. Review comment: NCDHW ---------------------------------------------------------------- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: [email protected] With regards, Apache Git Services
