TensorFlow.NET/test/TensorFlowNET.UnitTest/PythonTest.cs at master · bluelabs/TensorFlow.NET · GitHub

History

324 lines (288 loc) · 12.1 KB

Raw

100

101

102

103

104

105

106

107

108

109

110

111

112

113

114

115

116

117

118

119

120

121

122

123

124

125

126

127

128

129

130

131

132

133

134

135

136

137

138

139

140

141

142

143

144

145

146

147

148

149

150

151

152

153

154

155

156

157

158

159

160

161

162

163

164

165

166

167

168

169

170

171

172

173

174

175

176

177

178

179

180

181

182

183

184

185

186

187

188

189

190

191

192

193

194

195

196

197

198

199

200

201

202

203

204

205

206

207

208

209

210

211

212

213

214

215

216

217

218

219

220

221

222

223

224

225

226

227

228

229

230

231

232

233

234

235

236

237

238

239

240

241

242

243

244

245

246

247

248

249

250

251

252

253

254

255

256

257

258

259

260

261

262

263

264

265

266

267

268

269

270

271

272

273

274

275

276

277

278

279

280

281

282

283

284

285

286

287

288

289

290

291

292

293

294

295

296

297

298

299

300

301

302

303

304

305

306

307

308

309

310

311

312

313

314

315

316

317

318

319

320

321

322

323

324

using Microsoft.VisualStudio.TestTools.UnitTesting;

using Newtonsoft.Json.Linq;

using Tensorflow.NumPy;

using System;

using System.Collections;

using System.Linq;

using Tensorflow;

using static Tensorflow.Binding;

namespace TensorFlowNET.UnitTest

{

/// <summary>

/// Use as base class for test classes to get additional assertions

/// </summary>

public class PythonTest

{

#region python compatibility layer

protected PythonTest self { get => this; }

protected int None => -1;

#endregion

#region pytest assertions

public void assertItemsEqual(ICollection given, ICollection expected)

{

if (given is Hashtable && expected is Hashtable)

{

Assert.AreEqual(JObject.FromObject(expected).ToString(), JObject.FromObject(given).ToString());

return;

}

Assert.IsNotNull(expected);

Assert.IsNotNull(given);

var e = expected.OfType<object>().ToArray();

var g = given.OfType<object>().ToArray();

Assert.AreEqual(e.Length, g.Length, $"The collections differ in length expected {e.Length} but got {g.Length}");

for (int i = 0; i < e.Length; i++)

{

/*if (g[i] is NDArray && e[i] is NDArray)

assertItemsEqual((g[i] as NDArray).GetData<object>(), (e[i] as NDArray).GetData<object>());

else*/

if (e[i] is ICollection && g[i] is ICollection)

assertEqual(g[i], e[i]);

else

Assert.AreEqual(e[i], g[i], $"Items differ at index {i}, expected {e[i]} but got {g[i]}");

}

public void assertAllEqual(ICollection given, ICollection expected)

{

assertItemsEqual(given, expected);

}

public void assertFloat32Equal(float expected, float actual, string msg)

{

float eps = 1e-6f;

Assert.IsTrue(Math.Abs(expected - actual) < eps * Math.Max(1.0f, Math.Abs(expected)), $"{msg}: expected {expected} vs actual {actual}");

}

public void assertFloat64Equal(double expected, double actual, string msg)

{

double eps = 1e-16f;

Assert.IsTrue(Math.Abs(expected - actual) < eps * Math.Max(1.0f, Math.Abs(expected)), $"{msg}: expected {expected} vs actual {actual}");

}

public void AssetSequenceEqual(float[] expected, float[] actual)

{

float eps = 1e-5f;

for (int i = 0; i < expected.Length; i++)

Assert.IsTrue(Math.Abs(expected[i] - actual[i]) < eps * Math.Max(1.0f, Math.Abs(expected[i])), $"expected {expected} vs actual {actual}");

}

public void AssetSequenceEqual(double[] expected, double[] actual)

{

double eps = 1e-5f;

for (int i = 0; i < expected.Length; i++)

Assert.IsTrue(Math.Abs(expected[i] - actual[i]) < eps * Math.Max(1.0f, Math.Abs(expected[i])), $"expected {expected} vs actual {actual}");

}

public void assertEqual(object given, object expected)

{

/*if (given is NDArray && expected is NDArray)

{

assertItemsEqual((given as NDArray).GetData<object>(), (expected as NDArray).GetData<object>());

return;

}*/

if (given is Hashtable && expected is Hashtable)

{

Assert.AreEqual(JObject.FromObject(expected).ToString(), JObject.FromObject(given).ToString());

return;

}

if (given is ICollection && expected is ICollection)

{

assertItemsEqual(given as ICollection, expected as ICollection);

return;

}

if (given is float && expected is float)

{

assertFloat32Equal((float)expected, (float)given, "");

return;

}

if (given is double && expected is double)

{

assertFloat64Equal((double)expected, (double)given, "");

return;

}

Assert.AreEqual(expected, given);

}

public void assertEquals(object given, object expected)

{

assertEqual(given, expected);

}

public void assert(object given)

{

if (given is bool)

Assert.IsTrue((bool)given);

Assert.IsNotNull(given);

}

public void assertIsNotNone(object given)

{

Assert.IsNotNull(given);

}

public void assertFalse(bool cond)

{

Assert.IsFalse(cond);

}

public void assertTrue(bool cond)

{

Assert.IsTrue(cond);

}

public void assertAllClose(NDArray array1, NDArray array2, double eps = 1e-5)

{

Assert.IsTrue(np.allclose(array1, array2, rtol: eps));

}

public void assertAllClose(double value, NDArray array2, double eps = 1e-5)

{

var array1 = np.ones_like(array2) * value;

Assert.IsTrue(np.allclose(array1, array2, rtol: eps));

}

public void assertProtoEquals(object toProto, object o)

{

throw new NotImplementedException();

}

#endregion

#region tensor evaluation and test session

//protected object _eval_helper(Tensor[] tensors)

//{

// if (tensors == null)

// return null;

// return nest.map_structure(self._eval_tensor, tensors);

//}

protected object _eval_tensor(object tensor)

{

if (tensor == null)

return None;

//else if (callable(tensor))

// return self._eval_helper(tensor())

else

{

try

{

//TODO:

// if sparse_tensor.is_sparse(tensor):

// return sparse_tensor.SparseTensorValue(tensor.indices, tensor.values,

// tensor.dense_shape)

//return (tensor as Tensor).numpy();

}

catch (Exception)

{

throw new ValueError("Unsupported type: " + tensor.GetType());

}

return null;

}

/// <summary>

/// This function is used in many original tensorflow unit tests to evaluate tensors

/// in a test session with special settings (for instance constant folding off)

///

/// </summary>

public T evaluate<T>(Tensor tensor)

{

object result = null;

// if context.executing_eagerly():

// return self._eval_helper(tensors)

// else:

{

using (var sess = tf.Session())

{

var ndarray = tensor.eval(sess);

if (typeof(T) == typeof(double))

{

double x = ndarray;

result = x;

}

else if (typeof(T) == typeof(int))

{

int x = ndarray;

result = x;

}

else

{

result = ndarray;

}

return (T)result;

}

public Session cached_session()

{

throw new NotImplementedException();

}

//Returns a TensorFlow Session for use in executing tests.

public Session session(Graph graph = null, object config = null, bool use_gpu = false, bool force_gpu = false)

{

//Note that this will set this session and the graph as global defaults.

//Use the `use_gpu` and `force_gpu` options to control where ops are run.If

//`force_gpu` is True, all ops are pinned to `/device:GPU:0`. Otherwise, if

//`use_gpu` is True, TensorFlow tries to run as many ops on the GPU as

//possible.If both `force_gpu and `use_gpu` are False, all ops are pinned to

//the CPU.

//Example:

//```python

//class MyOperatorTest(test_util.TensorFlowTestCase):

// def testMyOperator(self):

// with self.session(use_gpu= True):

// valid_input = [1.0, 2.0, 3.0, 4.0, 5.0]

// result = MyOperator(valid_input).eval()

// self.assertEqual(result, [1.0, 2.0, 3.0, 5.0, 8.0]

// invalid_input = [-1.0, 2.0, 7.0]

// with self.assertRaisesOpError("negative input not supported"):

// MyOperator(invalid_input).eval()

//```

//Args:

// graph: Optional graph to use during the returned session.

// config: An optional config_pb2.ConfigProto to use to configure the

// session.

// use_gpu: If True, attempt to run as many ops as possible on GPU.

// force_gpu: If True, pin all ops to `/device:GPU:0`.

//Yields:

// A Session object that should be used as a context manager to surround

// the graph building and execution code in a test case.

Session s = null;

//if (context.executing_eagerly())

// yield None

//else

//{

s = self._create_session(graph, config, force_gpu);

//}

return s.as_default();

}

// See session() for details.

private Session _create_session(Graph graph, object cfg, bool forceGpu)

{

var prepare_config = new Func<object, object>((config) =>

{

// """Returns a config for sessions.

// Args:

// config: An optional config_pb2.ConfigProto to use to configure the

// session.

// Returns:

// A config_pb2.ConfigProto object.

//TODO: config

// # use_gpu=False. Currently many tests rely on the fact that any device

// # will be used even when a specific device is supposed to be used.

// allow_soft_placement = not force_gpu

// if config is None:

// config = config_pb2.ConfigProto()

// config.allow_soft_placement = allow_soft_placement

// config.gpu_options.per_process_gpu_memory_fraction = 0.3

// elif not allow_soft_placement and config.allow_soft_placement:

// config_copy = config_pb2.ConfigProto()

// config_copy.CopyFrom(config)

// config = config_copy

// config.allow_soft_placement = False

// # Don't perform optimizations for tests so we don't inadvertently run

// # gpu ops on cpu

// config.graph_options.optimizer_options.opt_level = -1

// # Disable Grappler constant folding since some tests & benchmarks

// # use constant input and become meaningless after constant folding.

// # DO NOT DISABLE GRAPPLER OPTIMIZERS WITHOUT CONSULTING WITH THE

// # GRAPPLER TEAM.

// config.graph_options.rewrite_options.constant_folding = (

// rewriter_config_pb2.RewriterConfig.OFF)

// config.graph_options.rewrite_options.pin_to_host_optimization = (

// rewriter_config_pb2.RewriterConfig.OFF)

return config;

});

//TODO: use this instead of normal session

//return new ErrorLoggingSession(graph = graph, config = prepare_config(config))

return new Session(graph);//, config = prepare_config(config))

}

#endregion

public void AssetSequenceEqual<T>(T[] a, T[] b)

{

Assert.IsTrue(Enumerable.SequenceEqual(a, b));

}

TensorFlow.NET/test/TensorFlowNET.UnitTest/PythonTest.cs at master · bluelabs/TensorFlow.NET · GitHub

Expand file tree

Breadcrumbs

PythonTest.cs

Latest commit

History

Breadcrumbs

PythonTest.cs

File metadata and controls