/dports/science/py-nibabel/nibabel-3.2.1/nibabel/cmdline/tests/ |
H A D | test_utils.py | 56 ("dim_info", [np.asarray(0).astype(dtype="uint8"), np.asarray(57).astype(dtype="uint8")]), 59 ("datatype", [np.array(2).astype(dtype="uint8"), np.array(4).astype(dtype="uint8")]), 60 ("bitpix", [np.array(8).astype(dtype="uint8"), np.array(16).astype(dtype="uint8")]), 64 ("slice_end", [np.array(0).astype(dtype="uint8"), np.array(23).astype(dtype="uint8")]), 65 ("xyzt_units", [np.array(0).astype(dtype="uint8"), np.array(10).astype(dtype="uint8")]), 69 ("qform_code", [np.array(0).astype(dtype="int16"), np.array(1).astype(dtype="int16")]), 70 ("sform_code", [np.array(2).astype(dtype="int16"), np.array(1).astype(dtype="int16")]), 94 ("datatype", [np.array(2).astype(dtype="uint8"), np.array(4).astype(dtype="uint8")]), 95 ("bitpix", [np.array(8).astype(dtype="uint8"), np.array(16).astype(dtype="uint8")]) 167 ("datatype", [np.array(2).astype(dtype="uint8"), np.array(4).astype(dtype="uint8")]), [all …]
|
/dports/misc/py-onnx/onnx-1.10.2/onnx/backend/test/case/node/ |
H A D | nonmaxsuppression.py | 31 ]]).astype(np.float32) 34 iou_threshold = np.array([0.5]).astype(np.float32) 54 ]]).astype(np.float32) 57 iou_threshold = np.array([0.5]).astype(np.float32) 77 ]]).astype(np.float32) 100 ]]).astype(np.float32) 118 ]]).astype(np.float32) 119 scores = np.array([[[0.9]]]).astype(np.float32) 146 ]]).astype(np.float32) 170 ]]).astype(np.float32) [all …]
|
H A D | split.py | 19 input = np.array([1., 2., 3., 4., 5., 6.]).astype(np.float32) 28 …ted_outputs = [np.array([1., 2.]).astype(np.float32), np.array([3., 4.]).astype(np.float32), np.ar… 31 split = np.array([2, 4]).astype(np.int64) 39 …expected_outputs = [np.array([1., 2.]).astype(np.float32), np.array([3., 4., 5., 6.]).astype(np.fl… 59 split = np.array([2, 4]).astype(np.int64) 83 …ted_outputs = [np.array([1., 2.]).astype(np.float32), np.array([3., 4.]).astype(np.float32), np.ar… 86 split = np.array([2, 4]).astype(np.int64) 93 …expected_outputs = [np.array([1., 2.]).astype(np.float32), np.array([3., 4., 5., 6.]).astype(np.fl… 98 input = np.array([]).astype(np.float32) 101 split = np.array([0, 0, 0]).astype(np.int64) [all …]
|
H A D | tfidfvectorizer.py | 64 ngram_counts = np.array([0, 4]).astype(np.int64) 65 ngram_indexes = np.array([0, 1, 2, 3, 4, 5, 6]).astype(np.int64) 86 ngram_counts = np.array([0, 4]).astype(np.int64) 87 ngram_indexes = np.array([0, 1, 2, 3, 4, 5, 6]).astype(np.int64) 106 output = np.array([1., 1., 1.]).astype(np.float32) 108 ngram_counts = np.array([0, 0]).astype(np.int64) 109 ngram_indexes = np.array([0, 1, 2]).astype(np.int64) 130 ngram_counts = np.array([0, 4]).astype(np.int64) 152 ngram_counts = np.array([0, 4]).astype(np.int64) 174 ngram_counts = np.array([0, 4]).astype(np.int64) [all …]
|
H A D | gemm.py | 36 a = np.random.ranf([3, 5]).astype(np.float32) 37 b = np.random.ranf([5, 4]).astype(np.float32) 38 c = np.zeros([1, 4]).astype(np.float32) 50 a = np.random.ranf([2, 10]).astype(np.float32) 63 a = np.random.ranf([2, 3]).astype(np.float32) 64 b = np.random.ranf([3, 4]).astype(np.float32) 65 c = np.array(3.14).astype(np.float32) 79 c = np.random.ranf([1]).astype(np.float32) 122 c = np.zeros([1, 4]).astype(np.float32) 137 c = np.zeros([1, 4]).astype(np.float32) [all …]
|
H A D | pow.py | 16 z = np.power(x, y).astype(x.dtype) 30 x = np.array([1, 2, 3]).astype(np.float32) 31 y = np.array([4, 5, 6]).astype(np.float32) 50 x = np.array([1, 2, 3]).astype(np.float32) 51 y = np.array(2).astype(np.float32) 77 y = np.array([4, 5, 6]).astype(np.int64) 82 x = np.array([1, 2, 3]).astype(np.int64) 89 y = np.array([4, 5, 6]).astype(np.int32) 94 x = np.array([1, 2, 3]).astype(np.int32) 112 x = np.array([1, 2, 3]).astype(np.int64) [all …]
|
H A D | convtranspose.py | 21 [6., 7., 8.]]]]).astype(np.float32) 28 [1., 1., 1.]]]]).astype(np.float32) 51 [1., 1., 1.]]]).astype(np.float32) 92 [1., 1., 1.]]]]]).astype(np.float32) 172 [6., 7., 8.]]]]).astype(np.float32) 179 [1., 1., 1.]]]]).astype(np.float32) 228 [6., 7., 8.]]]]).astype(np.float32) 235 [1., 1., 1.]]]]).astype(np.float32) 263 [3., 2., 6.]]]]).astype(np.float32) 265 [1., 9.]]]]).astype(np.float32) [all …]
|
H A D | batchnorm.py | 40 s = np.random.randn(3).astype(np.float32) 41 bias = np.random.randn(3).astype(np.float32) 42 mean = np.random.randn(3).astype(np.float32) 43 var = np.random.rand(3).astype(np.float32) 58 s = np.random.randn(3).astype(np.float32) 59 bias = np.random.randn(3).astype(np.float32) 61 var = np.random.rand(3).astype(np.float32) 80 s = np.random.randn(3).astype(np.float32) 83 var = np.random.rand(3).astype(np.float32) 103 s = np.random.randn(3).astype(np.float32) [all …]
|
H A D | mod.py | 70 x = np.array([-4, 7, 5, 4, -7, 8]).astype(np.int64) 71 y = np.array([2, -3, 8, -2, 3, 5]).astype(np.int64) 126 x = np.array([4, 7, 5]).astype(np.uint8) 127 y = np.array([2, 3, 8]).astype(np.uint8) 140 x = np.array([4, 7, 5]).astype(np.uint16) 141 y = np.array([2, 3, 8]).astype(np.uint16) 154 x = np.array([4, 7, 5]).astype(np.uint32) 155 y = np.array([2, 3, 8]).astype(np.uint32) 168 x = np.array([4, 7, 5]).astype(np.uint64) 169 y = np.array([2, 3, 8]).astype(np.uint64) [all …]
|
H A D | trilu.py | 55 k = np.array(-1).astype(np.int64) 78 k = np.array(-7).astype(np.int64) 101 k = np.array(2).astype(np.int64) 124 k = np.array(6).astype(np.int64) 175 k = np.array(-1).astype(np.int64) 204 k = np.array(1).astype(np.int64) 229 k = np.array(6).astype(np.int64) 270 k = np.array(-1).astype(np.int64) 318 k = np.array(2).astype(np.int64) 341 k = np.array(6).astype(np.int64) [all …]
|
H A D | softmaxcrossentropy.py | 107 x = np.random.rand(3, 5).astype(np.float32) 129 x = np.random.rand(3, 5).astype(np.float32) 151 x = np.random.rand(3, 5).astype(np.float32) 174 x = np.random.rand(3, 5).astype(np.float32) 197 x = np.random.rand(3, 5).astype(np.float32) 219 x = np.random.rand(3, 5).astype(np.float32) 241 x = np.random.rand(3, 5).astype(np.float32) 263 x = np.random.rand(3, 5).astype(np.float32) 329 x = np.random.rand(3, 5).astype(np.float32) 352 x = np.random.rand(3, 5).astype(np.float32) [all …]
|
H A D | and.py | 26 x = (np.random.randn(3, 4) > 0).astype(np.bool) 27 y = (np.random.randn(3, 4) > 0).astype(np.bool) 33 x = (np.random.randn(3, 4, 5) > 0).astype(np.bool) 34 y = (np.random.randn(3, 4, 5) > 0).astype(np.bool) 40 x = (np.random.randn(3, 4, 5, 6) > 0).astype(np.bool) 55 x = (np.random.randn(3, 4, 5) > 0).astype(np.bool) 56 y = (np.random.randn(5) > 0).astype(np.bool) 62 x = (np.random.randn(3, 4, 5) > 0).astype(np.bool) 63 y = (np.random.randn(4, 5) > 0).astype(np.bool) 70 y = (np.random.randn(5, 6) > 0).astype(np.bool) [all …]
|
H A D | or.py | 26 x = (np.random.randn(3, 4) > 0).astype(np.bool) 27 y = (np.random.randn(3, 4) > 0).astype(np.bool) 33 x = (np.random.randn(3, 4, 5) > 0).astype(np.bool) 34 y = (np.random.randn(3, 4, 5) > 0).astype(np.bool) 40 x = (np.random.randn(3, 4, 5, 6) > 0).astype(np.bool) 55 x = (np.random.randn(3, 4, 5) > 0).astype(np.bool) 56 y = (np.random.randn(5) > 0).astype(np.bool) 62 x = (np.random.randn(3, 4, 5) > 0).astype(np.bool) 63 y = (np.random.randn(4, 5) > 0).astype(np.bool) 70 y = (np.random.randn(5, 6) > 0).astype(np.bool) [all …]
|
H A D | xor.py | 26 x = (np.random.randn(3, 4) > 0).astype(np.bool) 27 y = (np.random.randn(3, 4) > 0).astype(np.bool) 33 x = (np.random.randn(3, 4, 5) > 0).astype(np.bool) 34 y = (np.random.randn(3, 4, 5) > 0).astype(np.bool) 40 x = (np.random.randn(3, 4, 5, 6) > 0).astype(np.bool) 55 x = (np.random.randn(3, 4, 5) > 0).astype(np.bool) 56 y = (np.random.randn(5) > 0).astype(np.bool) 62 x = (np.random.randn(3, 4, 5) > 0).astype(np.bool) 63 y = (np.random.randn(4, 5) > 0).astype(np.bool) 70 y = (np.random.randn(5, 6) > 0).astype(np.bool) [all …]
|
/dports/misc/glow/glow-f24d960e3cc80db95ac0bc17b1900dbf60ca044a/thirdparty/onnx/onnx/backend/test/case/node/ |
H A D | nonmaxsuppression.py | 29 ]]).astype(np.float32) 32 iou_threshold = np.array([0.5]).astype(np.float32) 52 ]]).astype(np.float32) 55 iou_threshold = np.array([0.5]).astype(np.float32) 75 ]]).astype(np.float32) 98 ]]).astype(np.float32) 116 ]]).astype(np.float32) 117 scores = np.array([[[0.9]]]).astype(np.float32) 144 ]]).astype(np.float32) 168 ]]).astype(np.float32) [all …]
|
H A D | tfidfvectorizer.py | 62 ngram_counts = np.array([0, 4]).astype(np.int64) 63 ngram_indexes = np.array([0, 1, 2, 3, 4, 5, 6]).astype(np.int64) 84 ngram_counts = np.array([0, 4]).astype(np.int64) 85 ngram_indexes = np.array([0, 1, 2, 3, 4, 5, 6]).astype(np.int64) 104 output = np.array([1., 1., 1.]).astype(np.float32) 106 ngram_counts = np.array([0, 0]).astype(np.int64) 107 ngram_indexes = np.array([0, 1, 2]).astype(np.int64) 128 ngram_counts = np.array([0, 4]).astype(np.int64) 150 ngram_counts = np.array([0, 4]).astype(np.int64) 172 ngram_counts = np.array([0, 4]).astype(np.int64) [all …]
|
H A D | split.py | 17 input = np.array([1., 2., 3., 4., 5., 6.]).astype(np.float32) 26 …ted_outputs = [np.array([1., 2.]).astype(np.float32), np.array([3., 4.]).astype(np.float32), np.ar… 37 …expected_outputs = [np.array([1., 2.]).astype(np.float32), np.array([3., 4., 5., 6.]).astype(np.fl… 43 [7., 8., 9., 10., 11., 12.]]).astype(np.float32) 52 expected_outputs = [np.array([[1., 2., 3.], [7., 8., 9.]]).astype(np.float32), 53 np.array([[4., 5., 6.], [10., 11., 12.]]).astype(np.float32)] 65 expected_outputs = [np.array([[1., 2.], [7., 8.]]).astype(np.float32), 66 np.array([[3., 4., 5., 6.], [9., 10., 11., 12.]]).astype(np.float32)] 72 input = np.array([1., 2., 3., 4., 5., 6.]).astype(np.float32) 81 …ted_outputs = [np.array([1., 2.]).astype(np.float32), np.array([3., 4.]).astype(np.float32), np.ar… [all …]
|
H A D | convtranspose.py | 19 [6., 7., 8.]]]]).astype(np.float32) 26 [1., 1., 1.]]]]).astype(np.float32) 49 [1., 1., 1.]]]).astype(np.float32) 54 [0., 1., 3., 3., 2.]]]).astype(np.float32) 90 [1., 1., 1.]]]]]).astype(np.float32) 170 [6., 7., 8.]]]]).astype(np.float32) 177 [1., 1., 1.]]]]).astype(np.float32) 226 [6., 7., 8.]]]]).astype(np.float32) 233 [1., 1., 1.]]]]).astype(np.float32) 261 [3., 2., 6.]]]]).astype(np.float32) [all …]
|
H A D | mod.py | 68 x = np.array([-4, 7, 5, 4, -7, 8]).astype(np.int64) 69 y = np.array([2, -3, 8, -2, 3, 5]).astype(np.int64) 110 x = np.array([-4, 7, 5, 4, -7, 8]).astype(np.int8) 124 x = np.array([4, 7, 5]).astype(np.uint8) 125 y = np.array([2, 3, 8]).astype(np.uint8) 138 x = np.array([4, 7, 5]).astype(np.uint16) 139 y = np.array([2, 3, 8]).astype(np.uint16) 152 x = np.array([4, 7, 5]).astype(np.uint32) 153 y = np.array([2, 3, 8]).astype(np.uint32) 166 x = np.array([4, 7, 5]).astype(np.uint64) [all …]
|
/dports/math/py-pandas/pandas-1.2.5/pandas/tests/frame/methods/ |
H A D | test_astype.py | 137 df.astype(dtype) 215 tm.assert_frame_equal(df.astype(dt3), df.astype(str)) 224 df.astype(dt4) 226 df.astype(dt5) 304 tm.assert_frame_equal(df.astype("int64").astype(dtype), expected1) 305 tm.assert_frame_equal(df.astype(dtype).astype("float64"), df) 315 tm.assert_frame_equal(df.astype("int64").astype(dtype), expected1) 324 tm.assert_frame_equal(df.astype("int64").astype(dtype), expected1) 332 tm.assert_frame_equal(df.astype("int64").astype(dtype), expected1) 342 expected = concat([a1.astype(dtype), a2.astype(dtype)], axis=1) [all …]
|
/dports/math/py-pandas/pandas-1.2.5/pandas/tests/series/ |
H A D | test_dtypes.py | 21 res = s.astype("category") 27 res = s.astype("category") 65 ser.astype("float64") 80 cmp(ser.astype("object"), expected) 92 result = ser.astype("object").astype("category") 94 result = ser.astype("object").astype(CategoricalDtype()) 108 ser.astype(Categorical) 110 ser.astype("object").astype(Categorical) 116 df.col1 = df.col1.astype("category") 138 s1 = s.reindex(new_index).astype(temp_dtype).astype(new_dtype) [all …]
|
/dports/math/py-pandas/pandas-1.2.5/pandas/tests/series/methods/ |
H A D | test_astype.py | 62 ser.astype(dt3) 66 ser.astype(dt4) 76 ser.astype(dt5) 137 s.astype(dtype) 163 s = s.astype("O") 168 s = s.astype("O") 176 s = s.astype("O") 209 s = ts.astype(str) 215 s = ts.astype(str) 301 s.astype(dtype) [all …]
|
/dports/math/py-pandas/pandas-1.2.5/pandas/tests/indexes/interval/ |
H A D | test_astype.py | 67 index.astype(dtype) 94 index.left.astype(subtype), index.right.astype(subtype), closed=index.closed 124 index.astype(dtype) 147 index.left.astype(subtype), index.right.astype(subtype), closed=index.closed 162 index.astype(dtype) 168 index.astype(dtype) 172 index.astype(dtype) 179 index.astype(dtype) 202 index.left.astype(subtype), index.right.astype(subtype), closed=index.closed 210 index.astype(dtype) [all …]
|
/dports/math/py-theano/Theano-1.0.5/theano/gpuarray/tests/ |
H A D | test_blas.py | 31 rand(3, 2).astype('float32'), 34 rand(3, 2).astype('float64'), 46 float16_data = [rand(3).astype('float16'), 48 rand(3, 3).astype('float16'), 49 rand(3).astype('float16'), 62 float16_data = [rand(3, 3).astype('float16'), 64 rand(3, 3).astype('float16'), 65 rand(3, 3).astype('float16'), 76 float16_data = [rand(3, 3).astype('float16'), 77 rand(3, 3).astype('float16')] [all …]
|
/dports/math/py-pandas/pandas-1.2.5/pandas/tests/indexes/ |
H A D | test_datetimelike.py | 31 assert index.equals(index.astype(object)) 61 assert idx.equals(idx.astype(object)) 62 assert idx.astype(object).equals(idx) 63 assert idx.astype(object).equals(idx.astype(object)) 98 assert idx.equals(idx.astype(object)) 99 assert idx.astype(object).equals(idx) 100 assert idx.astype(object).equals(idx.astype(object)) 150 assert idx.equals(idx.astype(object)) 151 assert idx.astype(object).equals(idx) 152 assert idx.astype(object).equals(idx.astype(object)) [all …]
|