|
| 1 | +"""GPU + dask+GPU backend coverage for issue #1933. |
| 2 | +
|
| 3 | +#1933 added ``_validate_predictor_sample_format`` and wired it into |
| 4 | +every IFD-read site (eager numpy, dask, GPU tiled, GPU stripped). The |
| 5 | +eager and dask paths are covered by ``test_predictor3_int_dtype_1933``; |
| 6 | +this module closes the GPU coverage gap. |
| 7 | +
|
| 8 | +The validator is invoked at two GPU sites: |
| 9 | +
|
| 10 | +* ``_backends/gpu.py:443`` -- the tiled eager GPU read path. Reached when |
| 11 | + the file is tiled and ``bps == file_dtype.itemsize * 8`` (so the |
| 12 | + bps_mismatch fallback at line 358 does not take over). |
| 13 | +* ``_backends/gpu.py:999`` -- the GDS chunked GPU path |
| 14 | + (``_read_geotiff_gpu_chunked_gds``). Reached when the file qualifies |
| 15 | + for direct disk->GPU decode. |
| 16 | +
|
| 17 | +The stripped GPU path falls back to CPU via ``_read_to_array`` and the |
| 18 | +CPU-side validator there fires; the dask+GPU non-GDS path delegates to |
| 19 | +``read_geotiff_dask`` which has its own validator (covered by the |
| 20 | +existing dask test). The two NEW call sites have no targeted tests. |
| 21 | +
|
| 22 | +A regression dropping either of those two validator calls would let |
| 23 | +malformed predictor=3 + integer tiled files decode silently to |
| 24 | +garbage bytes on GPU. The eager-test asserts the error path is wired |
| 25 | +on CPU; this module asserts the GPU dispatcher path is wired too. |
| 26 | +""" |
| 27 | +from __future__ import annotations |
| 28 | + |
| 29 | +import importlib.util |
| 30 | + |
| 31 | +import numpy as np |
| 32 | +import pytest |
| 33 | + |
| 34 | +from xrspatial.geotiff._compression import COMPRESSION_NONE |
| 35 | +from xrspatial.geotiff._dtypes import LONG, SHORT, numpy_to_tiff_dtype |
| 36 | +from xrspatial.geotiff._header import ( |
| 37 | + TAG_BITS_PER_SAMPLE, |
| 38 | + TAG_COMPRESSION, |
| 39 | + TAG_IMAGE_LENGTH, |
| 40 | + TAG_IMAGE_WIDTH, |
| 41 | + TAG_PHOTOMETRIC, |
| 42 | + TAG_PREDICTOR, |
| 43 | + TAG_SAMPLE_FORMAT, |
| 44 | + TAG_SAMPLES_PER_PIXEL, |
| 45 | + TAG_STRIP_BYTE_COUNTS, |
| 46 | + TAG_STRIP_OFFSETS, |
| 47 | + TAG_ROWS_PER_STRIP, |
| 48 | + TAG_TILE_BYTE_COUNTS, |
| 49 | + TAG_TILE_LENGTH, |
| 50 | + TAG_TILE_OFFSETS, |
| 51 | + TAG_TILE_WIDTH, |
| 52 | +) |
| 53 | +from xrspatial.geotiff._writer import ( |
| 54 | + _assemble_standard_layout, |
| 55 | + _write_stripped, |
| 56 | +) |
| 57 | + |
| 58 | + |
| 59 | +def _gpu_available() -> bool: |
| 60 | + if importlib.util.find_spec("cupy") is None: |
| 61 | + return False |
| 62 | + try: |
| 63 | + import cupy |
| 64 | + |
| 65 | + return bool(cupy.cuda.is_available()) |
| 66 | + except Exception: |
| 67 | + return False |
| 68 | + |
| 69 | + |
| 70 | +_HAS_GPU = _gpu_available() |
| 71 | +pytestmark = pytest.mark.skipif( |
| 72 | + not _HAS_GPU, reason="cupy + CUDA required", |
| 73 | +) |
| 74 | + |
| 75 | + |
| 76 | +def _build_predictor3_uint32_stripped_tiff(arr: np.ndarray) -> bytes: |
| 77 | + """Build a stripped TIFF: predictor=3 + uint32 SampleFormat=1. |
| 78 | +
|
| 79 | + Mirrors the helper in ``test_predictor3_int_dtype_1933`` so the GPU |
| 80 | + coverage gap can be exercised against the same shape of malformed |
| 81 | + file the eager test uses. Compression is COMPRESSION_NONE so the |
| 82 | + strip bytes are exactly the raw integer values. |
| 83 | + """ |
| 84 | + rel_off, bc, chunks = _write_stripped(arr, COMPRESSION_NONE, False) |
| 85 | + bits_per_sample, _ = numpy_to_tiff_dtype(arr.dtype) |
| 86 | + tags = [ |
| 87 | + (TAG_IMAGE_WIDTH, LONG, 1, arr.shape[1]), |
| 88 | + (TAG_IMAGE_LENGTH, LONG, 1, arr.shape[0]), |
| 89 | + (TAG_BITS_PER_SAMPLE, SHORT, 1, bits_per_sample), |
| 90 | + (TAG_COMPRESSION, SHORT, 1, COMPRESSION_NONE), |
| 91 | + (TAG_PHOTOMETRIC, SHORT, 1, 1), |
| 92 | + (TAG_SAMPLES_PER_PIXEL, SHORT, 1, 1), |
| 93 | + (TAG_SAMPLE_FORMAT, SHORT, 1, 1), |
| 94 | + (TAG_PREDICTOR, SHORT, 1, 3), |
| 95 | + (TAG_ROWS_PER_STRIP, SHORT, 1, arr.shape[0]), |
| 96 | + (TAG_STRIP_OFFSETS, LONG, len(rel_off), rel_off), |
| 97 | + (TAG_STRIP_BYTE_COUNTS, LONG, len(bc), bc), |
| 98 | + ] |
| 99 | + parts = [(arr, arr.shape[1], arr.shape[0], rel_off, bc, chunks)] |
| 100 | + return _assemble_standard_layout(8, [tags], parts, bigtiff=False) |
| 101 | + |
| 102 | + |
| 103 | +def _build_predictor3_uint32_tiled_tiff( |
| 104 | + arr: np.ndarray, tile_w: int = 16, tile_h: int = 16, |
| 105 | +) -> bytes: |
| 106 | + """Build a tiled malformed TIFF: predictor=3 + uint32 SampleFormat=1. |
| 107 | +
|
| 108 | + The tiled layout is the one that reaches the GPU validator at |
| 109 | + ``_backends/gpu.py:443`` (no bps_mismatch fallback). Tile size is |
| 110 | + 16x16, the smallest tifffile/standard tile size. |
| 111 | + """ |
| 112 | + bits_per_sample, _ = numpy_to_tiff_dtype(arr.dtype) |
| 113 | + h, w = arr.shape |
| 114 | + |
| 115 | + tiles_across = (w + tile_w - 1) // tile_w |
| 116 | + tiles_down = (h + tile_h - 1) // tile_h |
| 117 | + tiles: list[bytes] = [] |
| 118 | + rel_off: list[int] = [] |
| 119 | + bc: list[int] = [] |
| 120 | + offset = 0 |
| 121 | + for tr in range(tiles_down): |
| 122 | + for tc in range(tiles_across): |
| 123 | + r0 = tr * tile_h |
| 124 | + c0 = tc * tile_w |
| 125 | + r1 = min(r0 + tile_h, h) |
| 126 | + c1 = min(c0 + tile_w, w) |
| 127 | + tile_slice = arr[r0:r1, c0:c1] |
| 128 | + if tile_slice.shape != (tile_h, tile_w): |
| 129 | + padded = np.zeros((tile_h, tile_w), dtype=arr.dtype) |
| 130 | + padded[: tile_slice.shape[0], : tile_slice.shape[1]] = ( |
| 131 | + tile_slice) |
| 132 | + tile_arr = padded |
| 133 | + else: |
| 134 | + tile_arr = np.ascontiguousarray(tile_slice) |
| 135 | + chunk = tile_arr.tobytes() |
| 136 | + rel_off.append(offset) |
| 137 | + bc.append(len(chunk)) |
| 138 | + tiles.append(chunk) |
| 139 | + offset += len(chunk) |
| 140 | + |
| 141 | + tags = [ |
| 142 | + (TAG_IMAGE_WIDTH, LONG, 1, w), |
| 143 | + (TAG_IMAGE_LENGTH, LONG, 1, h), |
| 144 | + (TAG_BITS_PER_SAMPLE, SHORT, 1, bits_per_sample), |
| 145 | + (TAG_COMPRESSION, SHORT, 1, COMPRESSION_NONE), |
| 146 | + (TAG_PHOTOMETRIC, SHORT, 1, 1), |
| 147 | + (TAG_SAMPLES_PER_PIXEL, SHORT, 1, 1), |
| 148 | + (TAG_SAMPLE_FORMAT, SHORT, 1, 1), |
| 149 | + (TAG_PREDICTOR, SHORT, 1, 3), |
| 150 | + (TAG_TILE_WIDTH, LONG, 1, tile_w), |
| 151 | + (TAG_TILE_LENGTH, LONG, 1, tile_h), |
| 152 | + (TAG_TILE_OFFSETS, LONG, len(rel_off), rel_off), |
| 153 | + (TAG_TILE_BYTE_COUNTS, LONG, len(bc), bc), |
| 154 | + ] |
| 155 | + parts = [(arr, w, h, rel_off, bc, tiles)] |
| 156 | + return _assemble_standard_layout(8, [tags], parts, bigtiff=False) |
| 157 | + |
| 158 | + |
| 159 | +class TestGPUEagerRejectsMalformedFile: |
| 160 | + """``read_geotiff_gpu`` rejects predictor=3 + integer SampleFormat.""" |
| 161 | + |
| 162 | + def test_gpu_eager_stripped_raises(self, tmp_path): |
| 163 | + from xrspatial.geotiff import read_geotiff_gpu |
| 164 | + |
| 165 | + arr = np.array( |
| 166 | + [[1, 2, 3, 4], [5, 6, 7, 8]], dtype=np.uint32) |
| 167 | + path = tmp_path / "pred3_uint32_stripped.tif" |
| 168 | + path.write_bytes(_build_predictor3_uint32_stripped_tiff(arr)) |
| 169 | + with pytest.raises(ValueError, match="Predictor=3"): |
| 170 | + read_geotiff_gpu(str(path)) |
| 171 | + |
| 172 | + def test_gpu_eager_tiled_raises(self, tmp_path): |
| 173 | + """Tiled layout hits the tiled GPU validator at gpu.py:443. |
| 174 | +
|
| 175 | + Distinct from the stripped fallback path -- a regression |
| 176 | + dropping the line 443 call would leak through this test |
| 177 | + because the stripped path's validator lives in |
| 178 | + ``_read_to_array`` and would still raise. |
| 179 | + """ |
| 180 | + from xrspatial.geotiff import read_geotiff_gpu |
| 181 | + |
| 182 | + arr = np.arange(256, dtype=np.uint32).reshape(16, 16) |
| 183 | + path = tmp_path / "pred3_uint32_tiled.tif" |
| 184 | + path.write_bytes(_build_predictor3_uint32_tiled_tiff(arr)) |
| 185 | + with pytest.raises(ValueError, match="Predictor=3"): |
| 186 | + read_geotiff_gpu(str(path)) |
| 187 | + |
| 188 | + def test_gpu_dispatcher_eager_raises(self, tmp_path): |
| 189 | + """``open_geotiff(gpu=True)`` dispatcher rejects the file.""" |
| 190 | + from xrspatial.geotiff import open_geotiff |
| 191 | + |
| 192 | + arr = np.arange(64, dtype=np.uint32).reshape(8, 8) |
| 193 | + path = tmp_path / "pred3_uint32_dispatch.tif" |
| 194 | + path.write_bytes(_build_predictor3_uint32_stripped_tiff(arr)) |
| 195 | + with pytest.raises(ValueError, match="Predictor=3"): |
| 196 | + open_geotiff(str(path), gpu=True) |
| 197 | + |
| 198 | + |
| 199 | +class TestGPUChunkedRejectsMalformedFile: |
| 200 | + """The dask+GPU paths also reject predictor=3 + integer.""" |
| 201 | + |
| 202 | + def test_read_geotiff_gpu_chunked_stripped_raises(self, tmp_path): |
| 203 | + from xrspatial.geotiff import read_geotiff_gpu |
| 204 | + |
| 205 | + arr = np.arange(64, dtype=np.uint32).reshape(8, 8) |
| 206 | + path = tmp_path / "pred3_uint32_chunked_str.tif" |
| 207 | + path.write_bytes(_build_predictor3_uint32_stripped_tiff(arr)) |
| 208 | + with pytest.raises(ValueError, match="Predictor=3"): |
| 209 | + read_geotiff_gpu(str(path), chunks=4) |
| 210 | + |
| 211 | + def test_read_geotiff_gpu_chunked_tiled_raises(self, tmp_path): |
| 212 | + """Tiled chunked path: routes through ``_read_geotiff_gpu_chunked``. |
| 213 | +
|
| 214 | + With KvikIO usable, qualification calls |
| 215 | + ``_read_geotiff_gpu_chunked_gds`` which invokes the validator at |
| 216 | + gpu.py:999 during graph construction; without KvikIO, the CPU |
| 217 | + dask fallback raises with the same message. Either way the |
| 218 | + caller sees the malformed-file rejection. The test pins the |
| 219 | + contract rather than the dispatch detail. |
| 220 | + """ |
| 221 | + from xrspatial.geotiff import read_geotiff_gpu |
| 222 | + |
| 223 | + arr = np.arange(256, dtype=np.uint32).reshape(16, 16) |
| 224 | + path = tmp_path / "pred3_uint32_chunked_tiled.tif" |
| 225 | + path.write_bytes(_build_predictor3_uint32_tiled_tiff(arr)) |
| 226 | + with pytest.raises(ValueError, match="Predictor=3"): |
| 227 | + read_geotiff_gpu(str(path), chunks=16) |
| 228 | + |
| 229 | + def test_open_geotiff_chunks_gpu_dispatcher_raises(self, tmp_path): |
| 230 | + """``open_geotiff(chunks=, gpu=True)`` dispatcher rejects the file.""" |
| 231 | + from xrspatial.geotiff import open_geotiff |
| 232 | + |
| 233 | + arr = np.arange(256, dtype=np.uint32).reshape(16, 16) |
| 234 | + path = tmp_path / "pred3_uint32_chunked_dispatch.tif" |
| 235 | + path.write_bytes(_build_predictor3_uint32_tiled_tiff(arr)) |
| 236 | + with pytest.raises(ValueError, match="Predictor=3"): |
| 237 | + open_geotiff(str(path), chunks=8, gpu=True) |
| 238 | + |
| 239 | + |
| 240 | +class TestValidPredictor3StillWorksOnGPU: |
| 241 | + """A legitimate predictor=3 + float32 tiled file still decodes on GPU.""" |
| 242 | + |
| 243 | + def test_predictor3_float32_gpu_round_trip(self, tmp_path): |
| 244 | + tifffile = pytest.importorskip("tifffile") |
| 245 | + pytest.importorskip("imagecodecs") |
| 246 | + |
| 247 | + from xrspatial.geotiff import read_geotiff_gpu |
| 248 | + |
| 249 | + arr = np.linspace(-1.0, 1.0, 256, dtype=np.float32).reshape(16, 16) |
| 250 | + path = tmp_path / "pred3_float32_tiled.tif" |
| 251 | + tifffile.imwrite( |
| 252 | + str(path), arr, predictor=3, compression="deflate", |
| 253 | + tile=(16, 16)) |
| 254 | + |
| 255 | + result = read_geotiff_gpu(str(path)) |
| 256 | + assert result.dtype == np.float32 |
| 257 | + np.testing.assert_array_equal(result.data.get(), arr) |
| 258 | + |
| 259 | + def test_predictor3_float32_dask_gpu_round_trip(self, tmp_path): |
| 260 | + tifffile = pytest.importorskip("tifffile") |
| 261 | + pytest.importorskip("imagecodecs") |
| 262 | + |
| 263 | + from xrspatial.geotiff import read_geotiff_gpu |
| 264 | + |
| 265 | + arr = np.linspace(-1.0, 1.0, 256, dtype=np.float32).reshape(16, 16) |
| 266 | + path = tmp_path / "pred3_float32_dask.tif" |
| 267 | + tifffile.imwrite( |
| 268 | + str(path), arr, predictor=3, compression="deflate", |
| 269 | + tile=(16, 16)) |
| 270 | + |
| 271 | + result = read_geotiff_gpu(str(path), chunks=8) |
| 272 | + assert result.dtype == np.float32 |
| 273 | + np.testing.assert_array_equal(result.compute().data.get(), arr) |
| 274 | + |
| 275 | + |
| 276 | +class TestErrorMessageStable: |
| 277 | + """The GPU error wording matches the eager/dask wording. |
| 278 | +
|
| 279 | + Cross-backend error parity is a real concern -- a regression that |
| 280 | + fired the validator on GPU but with a different message would force |
| 281 | + callers to special-case the backend on ``except ValueError``. |
| 282 | + """ |
| 283 | + |
| 284 | + def test_gpu_error_message_matches_eager(self, tmp_path): |
| 285 | + from xrspatial.geotiff import open_geotiff, read_geotiff_gpu |
| 286 | + |
| 287 | + arr = np.arange(64, dtype=np.uint32).reshape(8, 8) |
| 288 | + path = tmp_path / "pred3_uint32_msg.tif" |
| 289 | + path.write_bytes(_build_predictor3_uint32_stripped_tiff(arr)) |
| 290 | + |
| 291 | + with pytest.raises(ValueError) as exc_eager: |
| 292 | + open_geotiff(str(path)) |
| 293 | + with pytest.raises(ValueError) as exc_gpu: |
| 294 | + read_geotiff_gpu(str(path)) |
| 295 | + |
| 296 | + assert str(exc_eager.value) == str(exc_gpu.value), ( |
| 297 | + "GPU and eager paths must surface the same Predictor=3 " |
| 298 | + "error message so callers can use a single except branch." |
| 299 | + ) |
0 commit comments