(self)
| 1402 | self.assertAllEqual(a2_val, [[1.0, 1.0]]) |
| 1403 | |
| 1404 | def testFeedAndFetch(self): |
| 1405 | with session.Session() as sess: |
| 1406 | for dtype in [ |
| 1407 | dtypes.float16, dtypes.float32, dtypes.float64, dtypes.int32, |
| 1408 | dtypes.uint8, dtypes.int16, dtypes.int8, dtypes.int64, dtypes.bool, |
| 1409 | dtypes.complex64, dtypes.complex128 |
| 1410 | ]: |
| 1411 | for shape in [(32, 4, 128), (37,), (2, 0, 6), (0, 0, 0)]: |
| 1412 | np_dtype = dtype.as_numpy_dtype |
| 1413 | |
| 1414 | feed_t = array_ops.placeholder(dtype=dtype, shape=shape) |
| 1415 | out_t = array_ops.identity(feed_t) |
| 1416 | |
| 1417 | np_array = np.random.randint(-10, 10, shape) |
| 1418 | |
| 1419 | if dtype == dtypes.bool: |
| 1420 | np_array = np_array > 0 |
| 1421 | elif dtype == dtypes.complex64: |
| 1422 | np_array = np.sqrt(np_array.astype(np_dtype)) |
| 1423 | elif dtype == dtypes.complex64: |
| 1424 | np_array = np.sqrt(np_array.astype(np_dtype)) |
| 1425 | else: |
| 1426 | np_array = np_array.astype(np_dtype) |
| 1427 | |
| 1428 | self.assertAllEqual(np_array, |
| 1429 | sess.run(out_t, feed_dict={ |
| 1430 | feed_t: np_array |
| 1431 | })) |
| 1432 | # Check that we can also get the feed back. |
| 1433 | self.assertAllEqual(np_array, |
| 1434 | sess.run(feed_t, feed_dict={ |
| 1435 | feed_t: np_array |
| 1436 | })) |
| 1437 | # Also check that we can get both back. |
| 1438 | out_v, feed_v = sess.run( |
| 1439 | [out_t, feed_t], feed_dict={ |
| 1440 | feed_t: np_array |
| 1441 | }) |
| 1442 | self.assertAllEqual(np_array, out_v) |
| 1443 | self.assertAllEqual(np_array, feed_v) |
| 1444 | |
| 1445 | feed_fetch_runner = sess.make_callable([out_t, feed_t], [feed_t]) |
| 1446 | out_v, feed_v = feed_fetch_runner(np_array) |
| 1447 | self.assertAllEqual(np_array, out_v) |
| 1448 | self.assertAllEqual(np_array, feed_v) |
| 1449 | |
| 1450 | def testMakeCallableOnTensorWithRunOptions(self): |
| 1451 | with session.Session() as sess: |
nothing calls this directly
no test coverage detected