def collate(self, batch):
packed = self.pack(batch, return_dict=True)
y = np.array(
packed.pop("y_list")) if "y" in self.dataset.signature else None
packed["a"] = self.dataset.a
output = to_mixed(**packed)
if len(output) == 1:
output = output[0]
if y is None:
return output
else:
return output, y
def collate(self, batch):
packed = self.pack(batch)
packed["a"] = self.dataset.a
y = packed.pop("y_list", None)
if y is not None:
y = np.array(y)
output = to_mixed(**packed)
output = sp_matrices_to_sp_tensors(output)
if len(output) == 1:
output = output[0]
if y is None:
return output
else:
return output, y
def collate(self, batch):
packed = self.pack(batch, return_dict=True)
y = np.array(packed.pop("y_list")) if "y" in self.dataset.signature else None
packed["a"] = self.dataset.a
output = to_mixed(**packed)
# Sparse matrices to SparseTensors
output = list(output)
for i in range(len(output)):
if sp.issparse(output[i]):
output[i] = sp_matrix_to_sp_tensor(output[i])
output = tuple(output)
if len(output) == 1:
output = output[0]
if y is None:
return output
else:
return output, y