/
BarracudaModelParamLoader.cs
551 lines (514 loc) · 24.8 KB
/
BarracudaModelParamLoader.cs
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
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
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
380
381
382
383
384
385
386
387
388
389
390
391
392
393
394
395
396
397
398
399
400
401
402
403
404
405
406
407
408
409
410
411
412
413
414
415
416
417
418
419
420
421
422
423
424
425
426
427
428
429
430
431
432
433
434
435
436
437
438
439
440
441
442
443
444
445
446
447
448
449
450
451
452
453
454
455
456
457
458
459
460
461
462
463
464
465
466
467
468
469
470
471
472
473
474
475
476
477
478
479
480
481
482
483
484
485
486
487
488
489
490
491
492
493
494
495
496
497
498
499
500
501
502
503
504
505
506
507
508
509
510
511
512
513
514
515
516
517
518
519
520
521
522
523
524
525
526
527
528
529
530
531
532
533
534
535
536
537
538
539
540
541
542
543
544
545
546
547
548
549
550
551
using System;
using System.Collections.Generic;
using System.Linq;
using Unity.Barracuda;
using Unity.MLAgents.Actuators;
using Unity.MLAgents.Sensors;
using Unity.MLAgents.Policies;
namespace Unity.MLAgents.Inference
{
/// <summary>
/// Prepares the Tensors for the Learning Brain and exposes a list of failed checks if Model
/// and BrainParameters are incompatible.
/// </summary>
internal class BarracudaModelParamLoader
{
const long k_ApiVersion = 2;
/// <summary>
/// Factory for the ModelParamLoader : Creates a ModelParamLoader and runs the checks
/// on it.
/// </summary>
/// <param name="model">
/// The Barracuda engine model for loading static parameters
/// </param>
/// <param name="brainParameters">
/// The BrainParameters that are used verify the compatibility with the InferenceEngine
/// </param>
/// <param name="sensorComponents">Attached sensor components</param>
/// <param name="actuatorComponents">Attached actuator components</param>
/// <param name="observableAttributeTotalSize">Sum of the sizes of all ObservableAttributes.</param>
/// <param name="behaviorType">BehaviorType or the Agent to check.</param>
/// <returns>The list the error messages of the checks that failed</returns>
public static IEnumerable<string> CheckModel(Model model, BrainParameters brainParameters,
SensorComponent[] sensorComponents, ActuatorComponent[] actuatorComponents,
int observableAttributeTotalSize = 0,
BehaviorType behaviorType = BehaviorType.Default)
{
List<string> failedModelChecks = new List<string>();
if (model == null)
{
var errorMsg = "There is no model for this Brain; cannot run inference. ";
if (behaviorType == BehaviorType.InferenceOnly)
{
errorMsg += "Either assign a model, or change to a different Behavior Type.";
}
else
{
errorMsg += "(But can still train)";
}
failedModelChecks.Add(errorMsg);
return failedModelChecks;
}
var hasExpectedTensors = model.CheckExpectedTensors(failedModelChecks);
if (!hasExpectedTensors)
{
return failedModelChecks;
}
var modelApiVersion = (int)model.GetTensorByName(TensorNames.VersionNumber)[0];
if (modelApiVersion == -1)
{
failedModelChecks.Add(
"Model was not trained using the right version of ML-Agents. " +
"Cannot use this model.");
return failedModelChecks;
}
if (modelApiVersion != k_ApiVersion)
{
failedModelChecks.Add(
$"Version of the trainer the model was trained with ({modelApiVersion}) " +
$"is not compatible with the Brain's version ({k_ApiVersion}).");
return failedModelChecks;
}
var memorySize = (int)model.GetTensorByName(TensorNames.MemorySize)[0];
if (memorySize == -1)
{
failedModelChecks.Add($"Missing node in the model provided : {TensorNames.MemorySize}");
return failedModelChecks;
}
failedModelChecks.AddRange(
CheckInputTensorPresence(model, brainParameters, memorySize, sensorComponents)
);
failedModelChecks.AddRange(
CheckOutputTensorPresence(model, memorySize)
);
failedModelChecks.AddRange(
CheckInputTensorShape(model, brainParameters, sensorComponents, observableAttributeTotalSize)
);
failedModelChecks.AddRange(
CheckOutputTensorShape(model, brainParameters, actuatorComponents)
);
return failedModelChecks;
}
/// <summary>
/// Generates failed checks that correspond to inputs expected by the model that are not
/// present in the BrainParameters.
/// </summary>
/// <param name="model">
/// The Barracuda engine model for loading static parameters
/// </param>
/// <param name="brainParameters">
/// The BrainParameters that are used verify the compatibility with the InferenceEngine
/// </param>
/// <param name="memory">
/// The memory size that the model is expecting.
/// </param>
/// <param name="sensorComponents">Array of attached sensor components</param>
/// <returns>
/// A IEnumerable of string corresponding to the failed input presence checks.
/// </returns>
static IEnumerable<string> CheckInputTensorPresence(
Model model,
BrainParameters brainParameters,
int memory,
SensorComponent[] sensorComponents
)
{
var failedModelChecks = new List<string>();
var tensorsNames = model.GetInputNames();
// If there is no Vector Observation Input but the Brain Parameters expect one.
if ((brainParameters.VectorObservationSize != 0) &&
(!tensorsNames.Contains(TensorNames.VectorObservationPlaceholder)))
{
failedModelChecks.Add(
"The model does not contain a Vector Observation Placeholder Input. " +
"You must set the Vector Observation Space Size to 0.");
}
// If there are not enough Visual Observation Input compared to what the
// sensors expect.
var visObsIndex = 0;
for (var sensorIndex = 0; sensorIndex < sensorComponents.Length; sensorIndex++)
{
var sensor = sensorComponents[sensorIndex];
if (sensor.GetObservationShape().Length == 3)
{
if (!tensorsNames.Contains(
TensorNames.VisualObservationPlaceholderPrefix + visObsIndex))
{
failedModelChecks.Add(
"The model does not contain a Visual Observation Placeholder Input " +
$"for sensor component {visObsIndex} ({sensor.GetType().Name}).");
}
visObsIndex++;
}
if (sensor.GetObservationShape().Length == 2)
{
if (!tensorsNames.Contains(
TensorNames.ObservationPlaceholderPrefix + sensorIndex))
{
failedModelChecks.Add(
"The model does not contain an Observation Placeholder Input " +
$"for sensor component {sensorIndex} ({sensor.GetType().Name}).");
}
}
}
var expectedVisualObs = model.GetNumVisualInputs();
// Check if there's not enough visual sensors (too many would be handled above)
if (expectedVisualObs > visObsIndex)
{
failedModelChecks.Add(
$"The model expects {expectedVisualObs} visual inputs," +
$" but only found {visObsIndex} visual sensors."
);
}
// If the model has a non-negative memory size but requires a recurrent input
if (memory > 0)
{
if (!tensorsNames.Any(x => x.EndsWith("_h")) ||
!tensorsNames.Any(x => x.EndsWith("_c")))
{
failedModelChecks.Add(
"The model does not contain a Recurrent Input Node but has memory_size.");
}
}
// If the model uses discrete control but does not have an input for action masks
if (model.HasDiscreteOutputs())
{
if (!tensorsNames.Contains(TensorNames.ActionMaskPlaceholder))
{
failedModelChecks.Add(
"The model does not contain an Action Mask but is using Discrete Control.");
}
}
return failedModelChecks;
}
/// <summary>
/// Generates failed checks that correspond to outputs expected by the model that are not
/// present in the BrainParameters.
/// </summary>
/// <param name="model">
/// The Barracuda engine model for loading static parameters
/// </param>
/// <param name="memory">The memory size that the model is expecting/</param>
/// <returns>
/// A IEnumerable of string corresponding to the failed output presence checks.
/// </returns>
static IEnumerable<string> CheckOutputTensorPresence(Model model, int memory)
{
var failedModelChecks = new List<string>();
// If there is no Recurrent Output but the model is Recurrent.
if (memory > 0)
{
var memOutputs = model.memories.Select(x => x.output).ToList();
if (!memOutputs.Any(x => x.EndsWith("_h")) ||
!memOutputs.Any(x => x.EndsWith("_c")))
{
failedModelChecks.Add(
"The model does not contain a Recurrent Output Node but has memory_size.");
}
}
return failedModelChecks;
}
/// <summary>
/// Checks that the shape of the visual observation input placeholder is the same as the corresponding sensor.
/// </summary>
/// <param name="tensorProxy">The tensor that is expected by the model</param>
/// <param name="sensorComponent">The sensor that produces the visual observation.</param>
/// <returns>
/// If the Check failed, returns a string containing information about why the
/// check failed. If the check passed, returns null.
/// </returns>
static string CheckVisualObsShape(
TensorProxy tensorProxy, SensorComponent sensorComponent)
{
var shape = sensorComponent.GetObservationShape();
var heightBp = shape[0];
var widthBp = shape[1];
var pixelBp = shape[2];
var heightT = tensorProxy.Height;
var widthT = tensorProxy.Width;
var pixelT = tensorProxy.Channels;
if ((widthBp != widthT) || (heightBp != heightT) || (pixelBp != pixelT))
{
return $"The visual Observation of the model does not match. " +
$"Received TensorProxy of shape [?x{widthBp}x{heightBp}x{pixelBp}] but " +
$"was expecting [?x{widthT}x{heightT}x{pixelT}].";
}
return null;
}
/// <summary>
/// Checks that the shape of the rank 2 observation input placeholder is the same as the corresponding sensor.
/// </summary>
/// <param name="tensorProxy">The tensor that is expected by the model</param>
/// <param name="sensorComponent">The sensor that produces the visual observation.</param>
/// <returns>
/// If the Check failed, returns a string containing information about why the
/// check failed. If the check passed, returns null.
/// </returns>
static string CheckRankTwoObsShape(
TensorProxy tensorProxy, SensorComponent sensorComponent)
{
var shape = sensorComponent.GetObservationShape();
var dim1Bp = shape[0];
var dim2Bp = shape[1];
var dim1T = tensorProxy.Channels;
var dim2T = tensorProxy.Width;
if ((dim1Bp != dim1T) || (dim2Bp != dim2T))
{
return $"An Observation of the model does not match. " +
$"Received TensorProxy of shape [?x{dim1Bp}x{dim2Bp}] but " +
$"was expecting [?x{dim1T}x{dim2T}].";
}
return null;
}
/// <summary>
/// Generates failed checks that correspond to inputs shapes incompatibilities between
/// the model and the BrainParameters.
/// </summary>
/// <param name="model">
/// The Barracuda engine model for loading static parameters
/// </param>
/// <param name="brainParameters">
/// The BrainParameters that are used verify the compatibility with the InferenceEngine
/// </param>
/// <param name="sensorComponents">Attached sensors</param>
/// <param name="observableAttributeTotalSize">Sum of the sizes of all ObservableAttributes.</param>
/// <returns>The list the error messages of the checks that failed</returns>
static IEnumerable<string> CheckInputTensorShape(
Model model, BrainParameters brainParameters, SensorComponent[] sensorComponents,
int observableAttributeTotalSize)
{
var failedModelChecks = new List<string>();
var tensorTester =
new Dictionary<string, Func<BrainParameters, TensorProxy, SensorComponent[], int, string>>()
{
{TensorNames.VectorObservationPlaceholder, CheckVectorObsShape},
{TensorNames.PreviousActionPlaceholder, CheckPreviousActionShape},
{TensorNames.RandomNormalEpsilonPlaceholder, ((bp, tensor, scs, i) => null)},
{TensorNames.ActionMaskPlaceholder, ((bp, tensor, scs, i) => null)},
{TensorNames.SequenceLengthPlaceholder, ((bp, tensor, scs, i) => null)},
{TensorNames.RecurrentInPlaceholder, ((bp, tensor, scs, i) => null)},
};
foreach (var mem in model.memories)
{
tensorTester[mem.input] = ((bp, tensor, scs, i) => null);
}
var visObsIndex = 0;
for (var sensorIndex = 0; sensorIndex < sensorComponents.Length; sensorIndex++)
{
var sensorComponent = sensorComponents[sensorIndex];
if (sensorComponent.GetObservationShape().Length == 3)
{
tensorTester[TensorNames.VisualObservationPlaceholderPrefix + visObsIndex] =
(bp, tensor, scs, i) => CheckVisualObsShape(tensor, sensorComponent);
visObsIndex++;
}
if (sensorComponent.GetObservationShape().Length == 2)
{
tensorTester[TensorNames.ObservationPlaceholderPrefix + sensorIndex] =
(bp, tensor, scs, i) => CheckRankTwoObsShape(tensor, sensorComponent);
}
}
// If the model expects an input but it is not in this list
foreach (var tensor in model.GetInputTensors())
{
if (!tensorTester.ContainsKey(tensor.name))
{
if (!tensor.name.Contains("visual_observation"))
{
failedModelChecks.Add(
"Model requires an unknown input named : " + tensor.name);
}
}
else
{
var tester = tensorTester[tensor.name];
var error = tester.Invoke(brainParameters, tensor, sensorComponents, observableAttributeTotalSize);
if (error != null)
{
failedModelChecks.Add(error);
}
}
}
return failedModelChecks;
}
/// <summary>
/// Checks that the shape of the Vector Observation input placeholder is the same in the
/// model and in the Brain Parameters.
/// </summary>
/// <param name="brainParameters">
/// The BrainParameters that are used verify the compatibility with the InferenceEngine
/// </param>
/// <param name="tensorProxy">The tensor that is expected by the model</param>
/// <param name="sensorComponents">Array of attached sensor components</param>
/// <param name="observableAttributeTotalSize">Sum of the sizes of all ObservableAttributes.</param>
/// <returns>
/// If the Check failed, returns a string containing information about why the
/// check failed. If the check passed, returns null.
/// </returns>
static string CheckVectorObsShape(
BrainParameters brainParameters, TensorProxy tensorProxy, SensorComponent[] sensorComponents,
int observableAttributeTotalSize)
{
var vecObsSizeBp = brainParameters.VectorObservationSize;
var numStackedVector = brainParameters.NumStackedVectorObservations;
var totalVecObsSizeT = tensorProxy.shape[tensorProxy.shape.Length - 1];
var totalVectorSensorSize = 0;
foreach (var sensorComp in sensorComponents)
{
if (sensorComp.GetObservationShape().Length == 1)
{
totalVectorSensorSize += sensorComp.GetObservationShape()[0];
}
}
totalVectorSensorSize += observableAttributeTotalSize;
if (vecObsSizeBp * numStackedVector + totalVectorSensorSize != totalVecObsSizeT)
{
var sensorSizes = "";
foreach (var sensorComp in sensorComponents)
{
if (sensorComp.GetObservationShape().Length == 1)
{
var vecSize = sensorComp.GetObservationShape()[0];
if (sensorSizes.Length == 0)
{
sensorSizes = $"[{vecSize}";
}
else
{
sensorSizes += $", {vecSize}";
}
}
}
sensorSizes += "]";
return $"Vector Observation Size of the model does not match. Was expecting {totalVecObsSizeT} " +
$"but received: \n" +
$"Vector observations: {vecObsSizeBp} x {numStackedVector}\n" +
$"Total [Observable] attributes: {observableAttributeTotalSize}\n" +
$"SensorComponent sizes: {sensorSizes}.";
}
return null;
}
/// <summary>
/// Checks that the shape of the Previous Vector Action input placeholder is the same in the
/// model and in the Brain Parameters.
/// </summary>
/// <param name="brainParameters">
/// The BrainParameters that are used verify the compatibility with the InferenceEngine
/// </param>
/// <param name="tensorProxy"> The tensor that is expected by the model</param>
/// <param name="sensorComponents">Array of attached sensor components (unused).</param>
/// <param name="observableAttributeTotalSize">Sum of the sizes of all ObservableAttributes (unused).</param>
/// <returns>If the Check failed, returns a string containing information about why the
/// check failed. If the check passed, returns null.</returns>
static string CheckPreviousActionShape(
BrainParameters brainParameters, TensorProxy tensorProxy,
SensorComponent[] sensorComponents, int observableAttributeTotalSize)
{
var numberActionsBp = brainParameters.ActionSpec.NumDiscreteActions;
var numberActionsT = tensorProxy.shape[tensorProxy.shape.Length - 1];
if (numberActionsBp != numberActionsT)
{
return "Previous Action Size of the model does not match. " +
$"Received {numberActionsBp} but was expecting {numberActionsT}.";
}
return null;
}
/// <summary>
/// Generates failed checks that correspond to output shapes incompatibilities between
/// the model and the BrainParameters.
/// </summary>
/// <param name="model">
/// The Barracuda engine model for loading static parameters
/// </param>
/// <param name="brainParameters">
/// The BrainParameters that are used verify the compatibility with the InferenceEngine
/// </param>
/// <param name="actuatorComponents">Array of attached actuator components.</param>
/// <returns>
/// A IEnumerable of string corresponding to the incompatible shapes between model
/// and BrainParameters.
/// </returns>
static IEnumerable<string> CheckOutputTensorShape(
Model model,
BrainParameters brainParameters,
ActuatorComponent[] actuatorComponents)
{
var failedModelChecks = new List<string>();
// If the model expects an output but it is not in this list
var modelContinuousActionSize = model.ContinuousOutputSize();
var continuousError = CheckContinuousActionOutputShape(brainParameters, actuatorComponents, modelContinuousActionSize);
if (continuousError != null)
{
failedModelChecks.Add(continuousError);
}
var modelSumDiscreteBranchSizes = model.DiscreteOutputSize();
var discreteError = CheckDiscreteActionOutputShape(brainParameters, actuatorComponents, modelSumDiscreteBranchSizes);
if (discreteError != null)
{
failedModelChecks.Add(discreteError);
}
return failedModelChecks;
}
/// <summary>
/// Checks that the shape of the discrete action output is the same in the
/// model and in the Brain Parameters.
/// </summary>
/// <param name="brainParameters">
/// The BrainParameters that are used verify the compatibility with the InferenceEngine
/// </param>
/// <param name="actuatorComponents">Array of attached actuator components.</param>
/// <param name="modelSumDiscreteBranchSizes">
/// The size of the discrete action output that is expected by the model.
/// </param>
/// <returns>
/// If the Check failed, returns a string containing information about why the
/// check failed. If the check passed, returns null.
/// </returns>
static string CheckDiscreteActionOutputShape(
BrainParameters brainParameters, ActuatorComponent[] actuatorComponents, int modelSumDiscreteBranchSizes)
{
// TODO: check each branch size instead of sum of branch sizes
var sumOfDiscreteBranchSizes = brainParameters.ActionSpec.SumOfDiscreteBranchSizes;
foreach (var actuatorComponent in actuatorComponents)
{
var actionSpec = actuatorComponent.ActionSpec;
sumOfDiscreteBranchSizes += actionSpec.SumOfDiscreteBranchSizes;
}
if (modelSumDiscreteBranchSizes != sumOfDiscreteBranchSizes)
{
return "Discrete Action Size of the model does not match. The BrainParameters expect " +
$"{sumOfDiscreteBranchSizes} but the model contains {modelSumDiscreteBranchSizes}.";
}
return null;
}
/// <summary>
/// Checks that the shape of the continuous action output is the same in the
/// model and in the Brain Parameters.
/// </summary>
/// <param name="brainParameters">
/// The BrainParameters that are used verify the compatibility with the InferenceEngine
/// </param>
/// <param name="actuatorComponents">Array of attached actuator components.</param>
/// <param name="modelContinuousActionSize">
/// The size of the continuous action output that is expected by the model.
/// </param>
/// <returns>If the Check failed, returns a string containing information about why the
/// check failed. If the check passed, returns null.</returns>
static string CheckContinuousActionOutputShape(
BrainParameters brainParameters, ActuatorComponent[] actuatorComponents, int modelContinuousActionSize)
{
var numContinuousActions = brainParameters.ActionSpec.NumContinuousActions;
foreach (var actuatorComponent in actuatorComponents)
{
var actionSpec = actuatorComponent.ActionSpec;
numContinuousActions += actionSpec.NumContinuousActions;
}
if (modelContinuousActionSize != numContinuousActions)
{
return "Continuous Action Size of the model does not match. The BrainParameters and ActuatorComponents expect " +
$"{numContinuousActions} but the model contains {modelContinuousActionSize}.";
}
return null;
}
}
}