optima2005 commented on a change in pull request #4551: [Relay] add max_pool3d
in relay and TF converter
URL: https://github.com/apache/incubator-tvm/pull/4551#discussion_r360631001
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File path: python/tvm/relay/frontend/tensorflow.py
##########
@@ -122,6 +122,71 @@ def _impl(inputs, attr, params):
return get_relay_op(name)(*inputs)
return _impl
+def _pool3d(name):
+ def _impl(inputs, attr, params):
+ attr['data_format'] = attr['data_format'].decode("utf-8")
+ flip_layout = False
+
+ input_shape = attr['_input_shapes'][inputs[0]]
+
+ if attr['data_format'] == 'NDHWC':
+ attr['kernel_shape'] = (attr['ksize'][1], attr['ksize'][2],
attr['ksize'][3])
+ attr['strides'] = (attr['strides'][1], attr['strides'][2],
attr['strides'][3])
+ elif attr['data_format'] == 'NCDHW':
+ attr['kernel_shape'] = (attr['ksize'][2], attr['ksize'][3],
attr['ksize'][4])
+ attr['strides'] = (attr['strides'][2], attr['strides'][3],
attr['strides'][4])
+ else:
+ msg = 'Value {} of attribute "data_format" of operator Pooling ' \
+ 'is not valid.'
+ raise tvm.error.OpAttributeInvalid(msg.format(attr['data_format']))
+ if attr['data_format'] == "NDHWC":
+ tmp_shape = attr['_input_shapes'][inputs[0]]
+ input_shape = [tmp_shape[ii] for ii in (0, 4, 1, 2, 3)]
+ inputs[0] = _op.transpose(inputs[0], axes=(0, 4, 1, 2, 3))
+ attr['data_format'] = "NCDHW"
+ flip_layout = True
+
+ attr['padding'] = attr['padding'].decode("utf-8")
+
+ if attr['padding'] == 'VALID':
+ attr['padding'] = [0, 0, 0, 0, 0, 0]
+ elif attr['padding'] == 'SAME':
+ stride_d, stride_h, stride_w = attr['strides']
+ kernel_d, kernel_h, kernel_w = attr['kernel_shape']
+ if attr['data_format'] == 'NDHWC':
+ in_d = input_shape[1]
+ in_h = input_shape[2]
+ in_w = input_shape[3]
+ else:
+ in_d = input_shape[2]
+ in_h = input_shape[3]
+ in_w = input_shape[4]
+ pad_d = _get_pad_pair(in_d, kernel_d, stride_d)
+ pad_v = _get_pad_pair(in_h, kernel_h, stride_h)
+ pad_h = _get_pad_pair(in_w, kernel_w, stride_w)
+
+ attr['padding'] = [pad_d[0], pad_v[0], pad_h[0], pad_d[1],
pad_v[1], pad_h[1]]
+ else:
+ msg = 'Value {} in attribute "padding" of operator Pooling is ' \
+ 'not valid.'
+ raise tvm.error.OpAttributeInvalid(msg.format(attr['padding']))
+
+ if name == "avg_pool":
+ attr['count_include_pad'] = False
+ attr['ceil_mode'] = False
+ attr['data_format'] = 'NCDHW'
Review comment:
This line is not necessory.
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