(self, chunk)
| 206 | return None |
| 207 | |
| 208 | def _validate_chunk(self, chunk): |
| 209 | if chunk is None: |
| 210 | log.warning("Fetcher function returned None") |
| 211 | return False |
| 212 | |
| 213 | assert len(chunk) == len(self._input_blob_names), \ |
| 214 | "Expecting data blob for each input" |
| 215 | for d in chunk: |
| 216 | assert isinstance(d, np.ndarray), \ |
| 217 | "Fetcher function must return a numpy array" |
| 218 | if not self._dont_rebatch: |
| 219 | j = 1 |
| 220 | for d in chunk[1:]: |
| 221 | assert d.shape[self._batch_columns[j]] == \ |
| 222 | chunk[0].shape[self._batch_columns[0]], \ |
| 223 | "Each returned input must have equal number of samples" |
| 224 | j += 1 |
| 225 | |
| 226 | if len(chunk) == 0: |
| 227 | log.warning("Worker provided zero length input") |
| 228 | return False |
| 229 | |
| 230 | return True |
| 231 | |
| 232 | def put(self, chunk, data_input_coordinator): |
| 233 | if not self._validate_chunk(chunk): |
no test coverage detected