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[PyTorch] [Frontend] Add support for 'aten::new_zeros' & 'aten::copy_' #9375

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[PyTorch] [Frontend] Add support for 'aten::new_zeros' & 'aten::copy_' #9375

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26 changes: 25 additions & 1 deletion python/tvm/relay/frontend/pytorch.py
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Original file line number Diff line number Diff line change
Expand Up @@ -670,6 +670,21 @@ def ones_like(self, inputs, input_types):

return out

def new_zeros(self, inputs, input_types):
data = inputs[1]

import torch

if not isinstance(data, (_expr.Expr, list, torch.Tensor, np.ndarray)):
msg = "Data type %s could not be parsed in zeros op" % (type(data))
raise AssertionError(msg)

if inputs[2] is not None:
dtype = _convert_dtype_value(inputs[2])
else:
dtype = input_types[0]
return self.full_impl(data, 0, dtype)

def zeros(self, inputs, input_types):
data = inputs[0]

Expand Down Expand Up @@ -1305,7 +1320,10 @@ def tensortonum(self, inputs, input_types):
return inputs[0]

def view(self, inputs, input_types):
data = inputs[0]
if isinstance(inputs[0], _expr.Expr):
data = inputs[0]
else:
data = _op.cast(_wrap_const(inputs[0]), input_types[0])

if len(inputs) == 3:
shape_inp = [inputs[1], self.infer_shape(inputs[2])[0]]
Expand Down Expand Up @@ -1384,6 +1402,10 @@ def clone(self, inputs, input_types):
data = inputs[0]
return _op.tensor.copy(data)

def copy(self, inputs, input_types):
src = inputs[1]
return _op.tensor.copy(src)

def log_softmax(self, inputs, input_types):
data = inputs[0]
axis = int(inputs[1])
Expand Down Expand Up @@ -2819,6 +2841,7 @@ def create_convert_map(self):
"aten::addcmul": self.addcmul,
"aten::ones": self.ones,
"aten::ones_like": self.ones_like,
"aten::new_zeros": self.new_zeros,
"aten::zeros": self.zeros,
"aten::zeros_like": self.zeros_like,
"aten::full": self.full,
Expand Down Expand Up @@ -2878,6 +2901,7 @@ def create_convert_map(self):
"aten::view": self.view,
"aten::reshape": self.reshape,
"aten::clone": self.clone,
"aten::copy_": self.copy,
"aten::log_softmax": self.log_softmax,
"aten::sigmoid": self.sigmoid,
"aten::sigmoid_": self.sigmoid,
Expand Down