Coverage for mlprodict/npy/numpy_onnx_pyrt.py: 100%

1""" 

2@file 

3@brief :epkg:`numpy` functions implemented with :epkg:`onnx` 

4and compiled with this python runtime. 

5 

6.. versionadded:: 0.6 

7""" 

8import numpy 

9from .onnx_numpy_annotation import ( 

10 NDArrayType, 

11 NDArrayTypeSameShape, 

12 NDArraySameType, 

13 NDArraySameTypeSameShape) 

14from .numpy_onnx_impl import ( 

15 abs as nx_abs, 

16 acos as nx_acos, 

17 acosh as nx_acosh, 

18 amin as nx_min, 

19 amax as nx_max, 

20 arange as nx_arange, 

21 argmax as nx_argmax, 

22 argmin as nx_argmin, 

23 asin as nx_asin, 

24 asinh as nx_asinh, 

25 atan as nx_atan, 

26 atanh as nx_atanh, 

27 ceil as nx_ceil, 

28 clip as nx_clip, 

29 compress as nx_compress, 

30 cos as nx_cos, 

31 cosh as nx_cosh, 

32 cumsum as nx_cumsum, 

33 concat as nx_concat, 

34 det as nx_det, 

35 dot as nx_dot, 

36 einsum as nx_einsum, 

37 erf as nx_erf, 

38 exp as nx_exp, 

39 expit as nx_expit, 

40 expand_dims as nx_expand_dims, 

41 floor as nx_floor, 

42 hstack as nx_hstack, 

43 isnan as nx_isnan, 

44 log as nx_log, 

45 log1p as nx_log1p, 

46 matmul as nx_matmul, 

47 mean as nx_mean, 

48 pad as nx_pad, 

49 prod as nx_prod, 

50 reciprocal as nx_reciprocal, 

51 relu as nx_relu, 

52 round as nx_round, 

53 sigmoid as nx_sigmoid, 

54 sign as nx_sign, 

55 sin as nx_sin, 

56 sinh as nx_sinh, 

57 sqrt as nx_sqrt, 

58 squeeze as nx_squeeze, 

59 sum as nx_sum, 

60 tan as nx_tan, 

61 tanh as nx_tanh, 

62 topk as nx_topk, 

63 transpose as nx_transpose, 

64 unsqueeze as nx_unsqueeze, 

65 vstack as nx_vstack, 

66 where as nx_where, 

67) 

68from .onnx_numpy_wrapper import onnxnumpy_np 

69 

70 

71@onnxnumpy_np(signature=NDArraySameTypeSameShape("all")) 

72def abs(x): 

73 "abs" 

74 return nx_abs(x) 

75 

76 

77@onnxnumpy_np(signature=NDArraySameTypeSameShape("floats")) 

78def acos(x): 

79 "acos" 

80 return nx_acos(x) 

81 

82 

83@onnxnumpy_np(signature=NDArraySameTypeSameShape("floats")) 

84def acosh(x): 

85 "acosh" 

86 return nx_acosh(x) 

87 

88 

89@onnxnumpy_np(signature=NDArrayType((numpy.int64, numpy.int64))) 

90def arange(start, stop, step=1): 

91 "arange, *start*, *stop* must be specified." 

92 return nx_arange(start, stop, step=step) 

93 

94 

95@onnxnumpy_np(signature=NDArraySameType("all")) 

96def amax(x, axis=None, keepdims=0): 

97 "amax" 

98 return nx_max(x, axis=axis, keepdims=keepdims) 

99 

100 

101@onnxnumpy_np(signature=NDArraySameType("all")) 

102def amin(x, axis=None, keepdims=0): 

103 "amin" 

104 return nx_min(x, axis=axis, keepdims=keepdims) 

105 

106 

107@onnxnumpy_np(signature=NDArrayType("all_int")) 

108def argmax(x, axis=0, keepdims=0): 

109 "argmax" 

110 return nx_argmax(x, axis=axis, keepdims=keepdims) 

111 

112 

113@onnxnumpy_np(signature=NDArrayType("all_int")) 

114def argmin(x, axis=0, keepdims=0): 

115 "argmin" 

116 return nx_argmin(x, axis=axis, keepdims=keepdims) 

117 

118 

119@onnxnumpy_np(signature=NDArraySameTypeSameShape("floats")) 

120def asin(x): 

121 "asin" 

122 return nx_asin(x) 

123 

124 

125@onnxnumpy_np(signature=NDArraySameTypeSameShape("floats")) 

126def asinh(x): 

127 "asinh" 

128 return nx_asinh(x) 

129 

130 

131@onnxnumpy_np(signature=NDArraySameTypeSameShape("floats")) 

132def atan(x): 

133 "atan" 

134 return nx_atan(x) 

135 

136 

137@onnxnumpy_np(signature=NDArraySameTypeSameShape("floats")) 

138def atanh(x): 

139 "atanh" 

140 return nx_atanh(x) 

141 

142 

143@onnxnumpy_np(signature=NDArraySameTypeSameShape("floats")) 

144def ceil(x): 

145 "ceil" 

146 return nx_ceil(x) 

147 

148 

149@onnxnumpy_np( 

150 signature=NDArrayType(("all", "all", "all"), n_optional=2)) 

151def clip(x, a_min=None, a_max=None): 

152 "clip" 

153 return nx_clip(x, a_min, a_max) 

154 

155 

156@onnxnumpy_np(signature=NDArrayType(("bool", "T:all"), dtypes_out=('T',))) 

157def compress(condition, x, axis=None): 

158 "compress" 

159 return nx_compress(condition, x, axis=axis) 

160 

161 

162@onnxnumpy_np(signature=NDArrayType("all", nvars=True)) 

163def concat(*x, axis=0): 

164 "concat" 

165 return nx_concat(*x, axis=axis) 

166 

167 

168@onnxnumpy_np(signature=NDArraySameTypeSameShape("floats")) 

169def cos(x): 

170 "cos" 

171 return nx_cos(x) 

172 

173 

174@onnxnumpy_np(signature=NDArraySameTypeSameShape("floats")) 

175def cosh(x): 

176 "cosh" 

177 return nx_cosh(x) 

178 

179 

180@onnxnumpy_np(signature=NDArrayType(("all", "ints"))) 

181def cumsum(x, axis): 

182 "cumsum" 

183 return nx_cumsum(x, axis) 

184 

185 

186@onnxnumpy_np(signature=NDArrayType("all")) 

187def det(x): 

188 "det" 

189 return nx_det(x) 

190 

191 

192@onnxnumpy_np(signature=NDArrayType(("T:all", "T"))) 

193def dot(a, b): 

194 "dot" 

195 return nx_dot(a, b) 

196 

197 

198@onnxnumpy_np(signature=NDArrayType("all", nvars=True)) 

199def einsum(*x, equation=None): 

200 "einsum" 

201 return nx_einsum(*x, equation=equation) 

202 

203 

204@onnxnumpy_np(signature=NDArraySameTypeSameShape("floats")) 

205def erf(x): 

206 "erf" 

207 return nx_erf(x) 

208 

209 

210@onnxnumpy_np(signature=NDArraySameTypeSameShape("floats")) 

211def exp(x): 

212 "exp" 

213 return nx_exp(x) 

214 

215 

216@onnxnumpy_np(signature=NDArraySameTypeSameShape("floats")) 

217def expit(x): 

218 "expit" 

219 return nx_expit(x) 

220 

221 

222@onnxnumpy_np(signature=NDArrayType("floats")) 

223def expand_dims(x, axis=0): 

224 "expand_dims" 

225 return nx_expand_dims(x, axis) 

226 

227 

228@onnxnumpy_np(signature=NDArraySameTypeSameShape("floats")) 

229def floor(x): 

230 "floor" 

231 return nx_floor(x) 

232 

233 

234@onnxnumpy_np(signature=NDArrayType("all", nvars=True)) 

235def hstack(*x): 

236 "hstack" 

237 return nx_hstack(*x) 

238 

239 

240@onnxnumpy_np(signature=NDArrayTypeSameShape("all_bool")) 

241def isnan(x): 

242 "isnan" 

243 return nx_isnan(x) 

244 

245 

246@onnxnumpy_np(signature=NDArraySameTypeSameShape("floats")) 

247def log(x): 

248 "log" 

249 return nx_log(x) 

250 

251 

252@onnxnumpy_np(signature=NDArraySameTypeSameShape("floats")) 

253def log1p(x): 

254 "log1p" 

255 return nx_log1p(x) 

256 

257 

258@onnxnumpy_np(signature=NDArrayType(("T:all", "T"))) 

259def matmul(a, b): 

260 "matmul" 

261 return nx_matmul(a, b) 

262 

263 

264@onnxnumpy_np(signature=NDArrayType(("T:all", numpy.int64, 'T'), n_optional=1)) 

265def pad(x, pads, constant_value=None, mode='constant'): 

266 "pad" 

267 return nx_pad(x, pads, mode=mode, constant_value=constant_value) 

268 

269 

270@onnxnumpy_np(signature=NDArraySameType("all")) 

271def prod(x, axis=None, keepdims=0): 

272 "prod" 

273 return nx_prod(x, axis=axis, keepdims=keepdims) 

274 

275 

276@onnxnumpy_np(signature=NDArraySameType("all")) 

277def mean(x, axis=None, keepdims=0): 

278 "mean" 

279 return nx_mean(x, axis=axis, keepdims=keepdims) 

280 

281 

282@onnxnumpy_np(signature=NDArraySameTypeSameShape("floats")) 

283def reciprocal(x): 

284 "reciprocal" 

285 return nx_reciprocal(x) 

286 

287 

288@onnxnumpy_np(signature=NDArraySameTypeSameShape("floats")) 

289def relu(x): 

290 "relu" 

291 return nx_relu(x) 

292 

293 

294@onnxnumpy_np(signature=NDArraySameTypeSameShape("floats")) 

295def round(x): 

296 "round" 

297 return nx_round(x) 

298 

299 

300@onnxnumpy_np(signature=NDArraySameTypeSameShape("floats")) 

301def sigmoid(x): 

302 "expit" 

303 return nx_sigmoid(x) 

304 

305 

306@onnxnumpy_np(signature=NDArraySameTypeSameShape("floats")) 

307def sign(x): 

308 "sign" 

309 return nx_sign(x) 

310 

311 

312@onnxnumpy_np(signature=NDArraySameTypeSameShape("floats")) 

313def sin(x): 

314 "sin" 

315 return nx_sin(x) 

316 

317 

318@onnxnumpy_np(signature=NDArraySameTypeSameShape("floats")) 

319def sinh(x): 

320 "sinh" 

321 return nx_sinh(x) 

322 

323 

324@onnxnumpy_np(signature=NDArraySameTypeSameShape("floats")) 

325def sqrt(x): 

326 "sqrt" 

327 return nx_sqrt(x) 

328 

329 

330@onnxnumpy_np(signature=NDArrayType(("all", numpy.int64), n_optional=1)) 

331def squeeze(x, axis=None): 

332 "squeeze" 

333 return nx_squeeze(x, axis) 

334 

335 

336@onnxnumpy_np(signature=NDArraySameType("all")) 

337def sum(x, axis=None, keepdims=0): 

338 "sum" 

339 return nx_sum(x, axis=axis, keepdims=keepdims) 

340 

341 

342@onnxnumpy_np(signature=NDArraySameTypeSameShape("floats")) 

343def tan(x): 

344 "tan" 

345 return nx_tan(x) 

346 

347 

348@onnxnumpy_np(signature=NDArraySameTypeSameShape("floats")) 

349def tanh(x): 

350 "tanh" 

351 return nx_tanh(x) 

352 

353 

354@onnxnumpy_np(signature=NDArrayType(("T:all", "ints"), ("T", (numpy.int64,)))) 

355def topk(x, k, axis=-1, largest=1, sorted=1): 

356 "topk" 

357 return nx_topk(x, k, axis=axis, largest=largest, sorted=sorted) 

358 

359 

360@onnxnumpy_np(signature=NDArraySameType("all")) 

361def transpose(x, perm=(1, 0)): 

362 "transpose" 

363 return nx_transpose(x, perm=perm) 

364 

365 

366@onnxnumpy_np(signature=NDArrayType(("all", numpy.int64))) 

367def unsqueeze(x, axes): 

368 "unsqueeze" 

369 return nx_unsqueeze(x, axes) 

370 

371 

372@onnxnumpy_np(signature=NDArrayType("all", nvars=True)) 

373def vstack(*x): 

374 "vstack" 

375 return nx_vstack(*x) 

376 

377 

378@onnxnumpy_np(signature=NDArrayType(("bool", "T:all", "T"), ("T", ))) 

379def where(cond, x, y): 

380 "where" 

381 return nx_where(cond, x, y)