mshr-h commented on a change in pull request #8260:
URL: https://github.com/apache/tvm/pull/8260#discussion_r670054653
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File path: python/tvm/relay/frontend/caffe.py
##########
@@ -511,19 +511,72 @@ def convert_deconv(self, op):
if weight:
kh, kw = params["kernel_size"]
weight_shape = [-1, conv_params.num_output, kh, kw]
- weight_value = np.asarray(weight.data, np.float32)
+ if not weight.data:
+ if conv_params.weight_filler:
+ _filler = conv_params.weight_filler.value
+ weight_value = np.full(weight.shape.dim, _filler,
np.float32)
+ else:
+ raise tvm.error.OpAttributeInvalid("At least weight_filler
must be given")
+ else:
+ weight_value = np.asarray(weight.data, np.float32)
weight_value = np.reshape(weight_value, weight_shape)
else:
- raise Exception("No weight value of layer {} in
caffemodel".format(op.name))
+ raise tvm.error.OpAttributeRequired(
+ "No weight value of layer {} in caffemodel".format(op.name)
+ )
weight_expr = self.exp_tab.new_const(weight_value, dtype="float32")
in_expr = self.exp_tab.get_expr(inputs[0])
- out = _op.nn.conv2d_transpose(data=in_expr, weight=weight_expr,
**params)
- if bias:
+ groups = params["groups"]
+ channels = params["channels"]
+
+ if bias:
bias_value = np.asarray(bias.data, np.float32)
bias_expr = self.exp_tab.new_const(bias_value, dtype="float32")
- out = _op.nn.bias_add(out, bias_expr)
+
+ if groups > channels:
+ raise tvm.error.OpAttributeInvalid(
+ "Groups cannot be larger than the number of input channels"
+ )
+
+ if groups == channels:
Review comment:
If `groups == channels` and `groups==1` conditions are both true, it
goes into line 544. Is this behavior correct?
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