def load_pip_requirements(self, files_map=None, freeze=True):
        if files_map is None:
            files_map = self.default_pip_files
        for group, requirements_txt in files_map.items():
            path = Path(requirements_txt)
            if not path.exists() and group.lower() == "all" and freeze:
                cmd = envoy.run("pip freeze")
                self[group].loads(cmd.std_out)
            elif path.exists():
                self[group].load(path)
def __getitem__(self, index):

        img1 = self._read_img(self._image_list[index][0])
        img2 = self._read_img(self._image_list[index][1])

        if self._flow_list:  # it will be empty for some dataset when split="test"
            flow = self._read_flow(self._flow_list[index])
            if self._has_builtin_flow_mask:
                flow, valid_flow_mask = flow
            else:
                valid_flow_mask = None
        else:
            flow = valid_flow_mask = None

        if self.transforms is not None:
            img1, img2, flow, valid_flow_mask = self.transforms(img1, img2, flow, valid_flow_mask)

        if self._has_builtin_flow_mask or valid_flow_mask is not None:
            # The `or valid_flow_mask is not None` part is here because the mask can be generated within a transform
            return img1, img2, flow, valid_flow_mask
        else:
            return img1, img2, flow