(a, axis=None, keepdims=False, split_every=None, out=None)
| 300 | |
| 301 | @derived_from(np) |
| 302 | def nanmax(a, axis=None, keepdims=False, split_every=None, out=None): |
| 303 | if np.isnan(a.size): |
| 304 | raise ValueError(f"Arrays chunk sizes are unknown. {unknown_chunk_message}") |
| 305 | if a.size == 0: |
| 306 | raise ValueError( |
| 307 | "zero-size array to reduction operation fmax which has no identity" |
| 308 | ) |
| 309 | return reduction( |
| 310 | a, |
| 311 | _nanmax_skip, |
| 312 | _nanmax_skip, |
| 313 | axis=axis, |
| 314 | keepdims=keepdims, |
| 315 | dtype=a.dtype, |
| 316 | split_every=split_every, |
| 317 | out=out, |
| 318 | ) |
| 319 | |
| 320 | |
| 321 | def _nanmax_skip(x_chunk, axis, keepdims): |
nothing calls this directly
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