Lines Matching refs:array
20 # Tests of the array/buffer .get() factory method on unsupported dtype.
27 array = np.array([["hello", "goodbye"]])
29 attr = DenseElementsAttr.get(array)
31 # CHECK: unimplemented array format conversion from format:
38 array = np.array([[1, 2, 3], [4, 5, 6]], dtype=np.int64)
44 attr = DenseElementsAttr.get(array.view(np.datetime64),
50 print(np.array(attr))
205 array = np.array([[1.0, 1.0, 1.0], [1.0, 1.0, 1.0]], dtype=np.float32)
206 attr = DenseElementsAttr.get(array)
213 print(np.array(attr))
220 array = np.array([2.0, 1.0, 1.0], dtype=np.float32)
221 attr = DenseElementsAttr.get(array)
227 # Tests of the array/buffer .get() factory method, in all of its permutations.
236 array = np.array([[2, 4, 8], [16, 32, 64]], dtype=np.uint16)
237 attr = DenseElementsAttr.get(array, type=BF16Type.get())
247 array = np.array([[2, 4, 7], [-2, -4, -8]], dtype=np.int8)
248 attr = DenseElementsAttr.get(array, type=IntegerType.get_signless(4))
258 bool_array = np.array([[1, 0, 1], [0, 1, 0]], dtype=np.bool_)
259 array = np.packbits(bool_array, axis=None, bitorder="little")
261 array, type=IntegerType.get_signless(1), shape=bool_array.shape
270 zero = np.array(0, dtype=np.uint8)
271 one = np.array(255, dtype=np.uint8)
294 array = np.array([[2.0, 4.0, 8.0], [16.0, 32.0, 64.0]], dtype=np.float16)
295 attr = DenseElementsAttr.get(array)
300 print(np.array(attr))
307 array = np.array([[1.1, 2.2, 3.3], [4.4, 5.5, 6.6]], dtype=np.float32)
308 attr = DenseElementsAttr.get(array)
313 print(np.array(attr))
320 array = np.array([[1.1, 2.2, 3.3], [4.4, 5.5, 6.6]], dtype=np.float64)
321 attr = DenseElementsAttr.get(array)
326 print(np.array(attr))
334 array = np.array([True], dtype=np.bool_)
335 attr = DenseElementsAttr.get(array)
339 print(np.array(attr))
341 array = np.array([[True, False, True], [True, True, False]], dtype=np.bool_)
342 attr = DenseElementsAttr.get(array)
347 print(np.array(attr))
349 array = np.array(
352 attr = DenseElementsAttr.get(array)
357 print(np.array(attr))
359 array = np.array(
369 attr = DenseElementsAttr.get(array)
377 print(np.array(attr))
379 array = np.array(
386 attr = DenseElementsAttr.get(array)
391 print(np.array(attr))
393 array = np.array([], dtype=np.bool_)
394 attr = DenseElementsAttr.get(array)
398 print(np.array(attr))
406 array = np.array([[1, 2, 3], [4, 5, 6]], dtype=np.int16)
407 attr = DenseElementsAttr.get(array)
412 print(np.array(attr))
419 array = np.array([[1, 2, 3], [4, 5, 6]], dtype=np.uint16)
420 attr = DenseElementsAttr.get(array)
425 print(np.array(attr))
432 array = np.array([[1, 2, 3], [4, 5, 6]], dtype=np.int16)
433 attr = DenseElementsAttr.get(array, signless=False)
438 print(np.array(attr))
445 array = np.array([[1, 2, 3], [4, 5, 6]], dtype=np.uint16)
446 attr = DenseElementsAttr.get(array, signless=False)
451 print(np.array(attr))
459 array = np.array([[1, 2, 3], [4, 5, 6]], dtype=np.int32)
460 attr = DenseElementsAttr.get(array)
465 print(np.array(attr))
472 array = np.array([[1, 2, 3], [4, 5, 6]], dtype=np.uint32)
473 attr = DenseElementsAttr.get(array)
478 print(np.array(attr))
485 array = np.array([[1, 2, 3], [4, 5, 6]], dtype=np.int32)
486 attr = DenseElementsAttr.get(array, signless=False)
491 print(np.array(attr))
498 array = np.array([[1, 2, 3], [4, 5, 6]], dtype=np.uint32)
499 attr = DenseElementsAttr.get(array, signless=False)
504 print(np.array(attr))
512 array = np.array([[1, 2, 3], [4, 5, 6]], dtype=np.int64)
513 attr = DenseElementsAttr.get(array)
518 print(np.array(attr))
525 array = np.array([[1, 2, 3], [4, 5, 6]], dtype=np.uint64)
526 attr = DenseElementsAttr.get(array)
531 print(np.array(attr))
538 array = np.array([[1, 2, 3], [4, 5, 6]], dtype=np.int64)
539 attr = DenseElementsAttr.get(array, signless=False)
544 print(np.array(attr))
551 array = np.array([[1, 2, 3], [4, 5, 6]], dtype=np.uint64)
552 attr = DenseElementsAttr.get(array, signless=False)
557 print(np.array(attr))
565 array = np.array([[1, 2, 3], [4, 5, 6]], dtype=np.int64)
566 attr = DenseElementsAttr.get(array, type=idx_type)
569 arr = np.array(attr)
575 array = np.array([1, 2, 3], dtype=np.int64)
576 attr = DenseIntElementsAttr.get(array, type=VectorType.get([3], idx_type))
588 mview = memoryview(np.array([[1, 2, 3], [4, 5, 6]], dtype=np.int32))