| /dports/misc/py-onnx/onnx-1.10.2/onnx/backend/test/case/node/ |
| H A D | argmax.py | 26 if keepdims:
43 keepdims=keepdims)
63 keepdims=keepdims)
81 keepdims=keepdims)
84 result = argmax_use_numpy(data, keepdims=keepdims)
89 result = argmax_use_numpy(data, keepdims=keepdims)
102 keepdims=keepdims)
122 keepdims=keepdims,
143 keepdims=keepdims,
162 keepdims=keepdims,
[all …]
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| H A D | argmin.py | 26 if keepdims:
43 keepdims=keepdims)
63 keepdims=keepdims)
81 keepdims=keepdims)
84 result = argmin_use_numpy(data, keepdims=keepdims)
89 result = argmin_use_numpy(data, keepdims=keepdims)
102 keepdims=keepdims)
122 keepdims=keepdims,
143 keepdims=keepdims,
162 keepdims=keepdims,
[all …]
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| H A D | reducemax.py | 21 keepdims = 0
28 keepdims=keepdims)
31 reduced = np.maximum.reduce(data, axis=tuple(axes), keepdims=keepdims == 1)
49 keepdims = 1
56 keepdims=keepdims)
77 keepdims = 1
82 keepdims=keepdims)
85 reduced = np.maximum.reduce(data, axis=axes, keepdims=keepdims == 1)
93 reduced = np.maximum.reduce(data, axis=axes, keepdims=keepdims == 1)
101 keepdims = 1
[all …]
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| H A D | reduceprod.py | 21 keepdims = 0
28 keepdims=keepdims)
31 reduced = np.prod(data, axis=tuple(axes), keepdims=keepdims == 1)
41 reduced = np.prod(data, axis=tuple(axes), keepdims=keepdims == 1)
48 keepdims = 1
55 keepdims=keepdims)
75 keepdims = 1
81 keepdims=keepdims)
84 reduced = np.prod(data, axis=axes, keepdims=keepdims == 1)
92 reduced = np.prod(data, axis=axes, keepdims=keepdims == 1)
[all …]
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| H A D | reducemean.py | 21 keepdims = 0
28 keepdims=keepdims)
31 reduced = np.mean(data, axis=tuple(axes), keepdims=keepdims == 1)
41 reduced = np.mean(data, axis=tuple(axes), keepdims=keepdims == 1)
49 keepdims = 1
56 keepdims=keepdims)
77 keepdims = 1
83 keepdims=keepdims)
86 reduced = np.mean(data, axis=axes, keepdims=keepdims == 1)
94 reduced = np.mean(data, axis=axes, keepdims=keepdims == 1)
[all …]
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| H A D | reducemin.py | 21 keepdims = 0
28 keepdims=keepdims)
31 reduced = np.minimum.reduce(data, axis=tuple(axes), keepdims=keepdims == 1)
49 keepdims = 1
55 keepdims=keepdims)
76 keepdims = 1
82 keepdims=keepdims)
85 reduced = np.minimum.reduce(data, axis=axes, keepdims=keepdims == 1)
93 reduced = np.minimum.reduce(data, axis=axes, keepdims=keepdims == 1)
101 keepdims = 1
[all …]
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| H A D | reduce_log_sum_exp.py | 21 keepdims = 0
27 keepdims=keepdims
61 keepdims=keepdims
69 keepdims=keepdims == 1))
82 keepdims=keepdims == 1))
97 keepdims=keepdims
105 keepdims=keepdims == 1))
116 keepdims=keepdims == 1))
130 keepdims=keepdims
138 keepdims=keepdims == 1))
[all …]
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| H A D | reducesumsquare.py | 21 keepdims = 0
28 keepdims=keepdims)
31 reduced = np.sum(np.square(data), axis=tuple(axes), keepdims=keepdims == 1)
49 keepdims = 1
56 keepdims=keepdims)
77 keepdims = 1
83 keepdims=keepdims)
86 reduced = np.sum(np.square(data), axis=axes, keepdims=keepdims == 1)
94 reduced = np.sum(np.square(data), axis=axes, keepdims=keepdims == 1)
102 keepdims = 1
[all …]
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| H A D | reducesum.py | 21 keepdims = 0
27 keepdims=keepdims)
48 keepdims = 1
54 keepdims=keepdims)
75 keepdims = 1
81 keepdims=keepdims)
84 reduced = np.sum(data, axis=None, keepdims=keepdims == 1)
92 reduced = np.sum(data, axis=None, keepdims=keepdims == 1)
106 keepdims=keepdims)
121 axes.tolist()), keepdims=keepdims == 1)
[all …]
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| H A D | reducel1.py | 21 keepdims = 0
28 keepdims=keepdims
35 reduced = np.sum(a=np.abs(data), axis=tuple(axes), keepdims=keepdims == 1)
53 keepdims = 1
60 keepdims=keepdims
85 keepdims = 1
91 keepdims=keepdims
98 reduced = np.sum(a=np.abs(data), axis=axes, keepdims=keepdims == 1)
107 reduced = np.sum(a=np.abs(data), axis=axes, keepdims=keepdims == 1)
116 keepdims = 1
[all …]
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| H A D | reducel2.py | 21 keepdims = 0
28 keepdims=keepdims
36 a=np.square(data), axis=tuple(axes), keepdims=keepdims == 1))
48 a=np.square(data), axis=tuple(axes), keepdims=keepdims == 1))
57 keepdims = 1
64 keepdims=keepdims
92 keepdims = 1
98 keepdims=keepdims
106 a=np.square(data), axis=axes, keepdims=keepdims == 1))
116 a=np.square(data), axis=axes, keepdims=keepdims == 1))
[all …]
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| /dports/misc/mxnet/incubator-mxnet-1.9.0/python/mxnet/symbol/numpy/ |
| H A D | linalg.py | 215 return _npi.norm(x, ord=2, axis=None, keepdims=keepdims, flag=-2)
227 …rn _mx_sym_np.sum(_symbol.abs(x), axis=col_axis, keepdims=keepdims).max(axis=row_axis, keepdims=ke…
229 …rn _mx_sym_np.sum(_symbol.abs(x), axis=col_axis, keepdims=keepdims).min(axis=row_axis, keepdims=ke…
236 …rn _mx_sym_np.sum(_symbol.abs(x), axis=row_axis, keepdims=keepdims).max(axis=col_axis, keepdims=ke…
238 …rn _mx_sym_np.sum(_symbol.abs(x), axis=row_axis, keepdims=keepdims).min(axis=col_axis, keepdims=ke…
244 return _mx_sym_np.max(_symbol.abs(x), axis=axis, keepdims=keepdims)
247 return _mx_sym_np.min(_symbol.abs(x), axis=axis, keepdims=keepdims)
250 return _npi.norm(x, ord=2, axis=axis, keepdims=keepdims, flag=1)
252 return _npi.norm(x, ord=2, axis=axis, keepdims=keepdims, flag=-1)
254 return _npi.norm(x, ord=2, axis=axis, keepdims=keepdims, flag=2)
[all …]
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| /dports/misc/py-mxnet/incubator-mxnet-1.9.0/python/mxnet/symbol/numpy/ |
| H A D | linalg.py | 215 return _npi.norm(x, ord=2, axis=None, keepdims=keepdims, flag=-2)
227 …rn _mx_sym_np.sum(_symbol.abs(x), axis=col_axis, keepdims=keepdims).max(axis=row_axis, keepdims=ke…
229 …rn _mx_sym_np.sum(_symbol.abs(x), axis=col_axis, keepdims=keepdims).min(axis=row_axis, keepdims=ke…
236 …rn _mx_sym_np.sum(_symbol.abs(x), axis=row_axis, keepdims=keepdims).max(axis=col_axis, keepdims=ke…
238 …rn _mx_sym_np.sum(_symbol.abs(x), axis=row_axis, keepdims=keepdims).min(axis=col_axis, keepdims=ke…
244 return _mx_sym_np.max(_symbol.abs(x), axis=axis, keepdims=keepdims)
247 return _mx_sym_np.min(_symbol.abs(x), axis=axis, keepdims=keepdims)
250 return _npi.norm(x, ord=2, axis=axis, keepdims=keepdims, flag=1)
252 return _npi.norm(x, ord=2, axis=axis, keepdims=keepdims, flag=-1)
254 return _npi.norm(x, ord=2, axis=axis, keepdims=keepdims, flag=2)
[all …]
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| /dports/misc/tvm/incubator-tvm-0.6.1/topi/tests/python/ |
| H A D | test_topi_reduce.py | 26 if not keepdims:
52 B = topi.sum(A1, axis=axis, keepdims=keepdims)
54 B = topi.all(A, axis=axis, keepdims=keepdims)
56 B = topi.any(A, axis=axis, keepdims=keepdims)
58 B = topi.max(A1, axis=axis, keepdims=keepdims)
60 B = topi.min(A1, axis=axis, keepdims=keepdims)
62 B = topi.argmax(A1, axis=axis, keepdims=keepdims)
65 B = topi.argmin(A1, axis=axis, keepdims=keepdims)
88 out_npy = in_npy_map.sum(axis=axis, keepdims=keepdims)
90 out_npy = in_npy_map.all(axis=axis, keepdims=keepdims)
[all …]
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| /dports/misc/mxnet/incubator-mxnet-1.9.0/3rdparty/tvm/tests/python/topi/python/ |
| H A D | test_topi_reduce.py | 28 if not keepdims:
54 B = topi.sum(A1, axis=axis, keepdims=keepdims)
56 B = topi.all(A, axis=axis, keepdims=keepdims)
58 B = topi.any(A, axis=axis, keepdims=keepdims)
60 B = topi.max(A1, axis=axis, keepdims=keepdims)
62 B = topi.min(A1, axis=axis, keepdims=keepdims)
64 B = topi.argmax(A1, axis=axis, keepdims=keepdims)
67 B = topi.argmin(A1, axis=axis, keepdims=keepdims)
86 out_npy = in_npy_map.sum(axis=axis, keepdims=keepdims)
88 out_npy = in_npy_map.all(axis=axis, keepdims=keepdims)
[all …]
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| /dports/misc/py-tvm/incubator-tvm-0.6.1/topi/tests/python/ |
| H A D | test_topi_reduce.py | 26 if not keepdims:
52 B = topi.sum(A1, axis=axis, keepdims=keepdims)
54 B = topi.all(A, axis=axis, keepdims=keepdims)
56 B = topi.any(A, axis=axis, keepdims=keepdims)
58 B = topi.max(A1, axis=axis, keepdims=keepdims)
60 B = topi.min(A1, axis=axis, keepdims=keepdims)
62 B = topi.argmax(A1, axis=axis, keepdims=keepdims)
65 B = topi.argmin(A1, axis=axis, keepdims=keepdims)
88 out_npy = in_npy_map.sum(axis=axis, keepdims=keepdims)
90 out_npy = in_npy_map.all(axis=axis, keepdims=keepdims)
[all …]
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| /dports/misc/mxnet/incubator-mxnet-1.9.0/python/mxnet/ndarray/numpy/ |
| H A D | linalg.py | 214 return _npi.norm(x, ord=2, axis=None, keepdims=keepdims, flag=-2)
226 …n _mx_nd_np.sum(_mx_nd_np.abs(x), axis=col_axis, keepdims=keepdims).max(axis=row_axis, keepdims=ke…
228 …n _mx_nd_np.sum(_mx_nd_np.abs(x), axis=col_axis, keepdims=keepdims).min(axis=row_axis, keepdims=ke…
235 …n _mx_nd_np.sum(_mx_nd_np.abs(x), axis=row_axis, keepdims=keepdims).max(axis=col_axis, keepdims=ke…
237 …n _mx_nd_np.sum(_mx_nd_np.abs(x), axis=row_axis, keepdims=keepdims).min(axis=col_axis, keepdims=ke…
243 return _mx_nd_np.max(_mx_nd_np.abs(x), axis=axis, keepdims=keepdims)
247 return _npi.norm(x, ord=2, axis=axis, keepdims=keepdims, flag=1)
249 return _npi.norm(x, ord=2, axis=axis, keepdims=keepdims, flag=-1)
251 return _npi.norm(x, ord=2, axis=axis, keepdims=keepdims, flag=2)
253 return _npi.norm(x, ord=2, axis=axis, keepdims=keepdims, flag=1)
[all …]
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| /dports/misc/py-mxnet/incubator-mxnet-1.9.0/python/mxnet/ndarray/numpy/ |
| H A D | linalg.py | 214 return _npi.norm(x, ord=2, axis=None, keepdims=keepdims, flag=-2)
226 …n _mx_nd_np.sum(_mx_nd_np.abs(x), axis=col_axis, keepdims=keepdims).max(axis=row_axis, keepdims=ke…
228 …n _mx_nd_np.sum(_mx_nd_np.abs(x), axis=col_axis, keepdims=keepdims).min(axis=row_axis, keepdims=ke…
235 …n _mx_nd_np.sum(_mx_nd_np.abs(x), axis=row_axis, keepdims=keepdims).max(axis=col_axis, keepdims=ke…
237 …n _mx_nd_np.sum(_mx_nd_np.abs(x), axis=row_axis, keepdims=keepdims).min(axis=col_axis, keepdims=ke…
243 return _mx_nd_np.max(_mx_nd_np.abs(x), axis=axis, keepdims=keepdims)
247 return _npi.norm(x, ord=2, axis=axis, keepdims=keepdims, flag=1)
249 return _npi.norm(x, ord=2, axis=axis, keepdims=keepdims, flag=-1)
251 return _npi.norm(x, ord=2, axis=axis, keepdims=keepdims, flag=2)
253 return _npi.norm(x, ord=2, axis=axis, keepdims=keepdims, flag=1)
[all …]
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| /dports/misc/glow/glow-f24d960e3cc80db95ac0bc17b1900dbf60ca044a/thirdparty/onnx/onnx/backend/test/case/node/ |
| H A D | argmax.py | 15 if (keepdims == 1):
26 keepdims = 0
32 keepdims=keepdims)
34 result = argmax_use_numpy(data, axis=axis, keepdims=keepdims)
39 result = argmax_use_numpy(data, axis=axis, keepdims=keepdims)
46 keepdims = 1
52 keepdims=keepdims)
54 result = argmax_use_numpy(data, axis=axis, keepdims=keepdims)
70 keepdims=keepdims)
73 result = argmax_use_numpy(data, keepdims=keepdims)
[all …]
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| H A D | argmin.py | 15 if (keepdims == 1):
26 keepdims = 0
32 keepdims=keepdims)
34 result = argmin_use_numpy(data, axis=axis, keepdims=keepdims)
39 result = argmin_use_numpy(data, axis=axis, keepdims=keepdims)
46 keepdims = 1
52 keepdims=keepdims)
54 result = argmin_use_numpy(data, axis=axis, keepdims=keepdims)
70 keepdims=keepdims)
73 result = argmin_use_numpy(data, keepdims=keepdims)
[all …]
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| H A D | reducesum.py | 19 keepdims = 0
26 keepdims=keepdims)
29 reduced = np.sum(data, axis=tuple(axes), keepdims=keepdims == 1)
39 reduced = np.sum(data, axis=tuple(axes), keepdims=keepdims == 1)
47 keepdims = 1
54 keepdims=keepdims)
57 reduced = np.sum(data, axis=tuple(axes), keepdims=keepdims == 1)
75 keepdims = 1
81 keepdims=keepdims)
84 reduced = np.sum(data, axis=axes, keepdims=keepdims == 1)
[all …]
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| H A D | reducemin.py | 19 keepdims = 0
26 keepdims=keepdims)
29 reduced = np.minimum.reduce(data, axis=tuple(axes), keepdims=keepdims == 1)
39 reduced = np.minimum.reduce(data, axis=tuple(axes), keepdims=keepdims == 1)
47 keepdims = 1
53 keepdims=keepdims)
56 reduced = np.minimum.reduce(data, axis=tuple(axes), keepdims=keepdims == 1)
74 keepdims = 1
80 keepdims=keepdims)
83 reduced = np.minimum.reduce(data, axis=axes, keepdims=keepdims == 1)
[all …]
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| /dports/misc/py-tvm/incubator-tvm-0.6.1/python/tvm/relay/op/ |
| H A D | reduce.py | 53 return _make.argmax(data, axis, keepdims, exclude)
83 return _make.argmin(data, axis, keepdims, exclude)
114 return _make.sum(data, axis, keepdims, exclude)
166 return _make.all(data, axis, keepdims, exclude)
218 return _make.any(data, axis, keepdims, exclude)
249 return _make.max(data, axis, keepdims, exclude)
281 return _make.min(data, axis, keepdims, exclude)
312 return _make.mean(data, axis, keepdims, exclude)
409 if not keepdims:
444 if not keepdims:
[all …]
|
| /dports/misc/tvm/incubator-tvm-0.6.1/python/tvm/relay/op/ |
| H A D | reduce.py | 53 return _make.argmax(data, axis, keepdims, exclude)
83 return _make.argmin(data, axis, keepdims, exclude)
114 return _make.sum(data, axis, keepdims, exclude)
166 return _make.all(data, axis, keepdims, exclude)
218 return _make.any(data, axis, keepdims, exclude)
249 return _make.max(data, axis, keepdims, exclude)
281 return _make.min(data, axis, keepdims, exclude)
312 return _make.mean(data, axis, keepdims, exclude)
409 if not keepdims:
444 if not keepdims:
[all …]
|
| /dports/misc/mxnet/incubator-mxnet-1.9.0/3rdparty/tvm/python/tvm/relay/op/ |
| H A D | reduce.py | 54 return _make.argmax(data, axis, keepdims, exclude)
85 return _make.argmin(data, axis, keepdims, exclude)
116 return _make.sum(data, axis, keepdims, exclude)
168 return _make.all(data, axis, keepdims, exclude)
220 return _make.any(data, axis, keepdims, exclude)
251 return _make.max(data, axis, keepdims, exclude)
283 return _make.min(data, axis, keepdims, exclude)
417 if not keepdims:
452 if not keepdims:
488 def logsumexp(data, axis=None, keepdims=False): argument
[all …]
|