(self, code, idx=1)
| 123 | return ret, ret_imgs |
| 124 | |
| 125 | def wrap_code(self, code, idx=1): |
| 126 | s = sqrt_int(len(code)) |
| 127 | prefix = {8:'[TINY]', 16:'[SMALL]', 32:'[BASE]', 64:'[BIG]'}[s] |
| 128 | boi = {1:'[BOI1]', 2: '[BOI2]', 3:'[BOI3]'}[idx] |
| 129 | eoi = {1:'[EOI1]', 2: '[EOI2]', 3:'[EOI3]'}[idx] |
| 130 | |
| 131 | if isinstance(code, list): |
| 132 | return [self.command_tokens[prefix], self.command_tokens[boi]] + \ |
| 133 | code + [self.command_tokens[eoi]] |
| 134 | elif isinstance(code, np.ndarray): |
| 135 | return np.concatenate( |
| 136 | ( |
| 137 | np.array([self.command_tokens[prefix], self.command_tokens[boi]]), |
| 138 | code, |
| 139 | np.array([self.command_tokens[eoi]]) |
| 140 | ), |
| 141 | axis=0 |
| 142 | ) |
| 143 | elif isinstance(code, torch.Tensor): |
| 144 | return torch.cat( |
| 145 | ( |
| 146 | torch.tensor([self.command_tokens[prefix], self.command_tokens[boi]]), |
| 147 | code, |
| 148 | np.array([self.command_tokens[eoi]]) |
| 149 | ) |
| 150 | ) |
| 151 | else: |
| 152 | raise ValueError('') |
| 153 | |
| 154 | def parse_query(self, query, img_size=256): |
| 155 | text_buffer = [] |
no test coverage detected