zhutian
257 lines
8.3 KiB
Python
257 lines
8.3 KiB
Python
backend_opset_version = {
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'Abs': [1, 6],
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'Acos': [7],
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'Acosh': [9],
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'Adagrad': [],
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'Adam': [],
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'Add': [1, 6, 7],
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'And': [1, 7],
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'ArgMax': [1, 11, 12],
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'ArgMin': [1, 11, 12],
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'ArrayFeatureExtractor': [],
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'Asin': [7],
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'Asinh': [9],
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'Atan': [7],
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'Atanh': [9],
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'AveragePool': [1, 7, 10, 11],
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'BatchNormalization': [1, 6, 7, 9],
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'Binarizer': [],
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'BitShift': [11],
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'Cast': [1, 6, 9],
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'CastMap': [],
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'CategoryMapper': [],
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'Ceil': [1, 6],
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'Celu': [],
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'Clip': [1, 6, 11, 12],
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'Compress': [9, 11],
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'Concat': [1, 4, 11],
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'ConcatFromSequence': [],
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'Constant': [1, 9, 11, 12],
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'ConstantFill': [1],
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'ConstantOfShape': [9],
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'Conv': [1, 11],
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'ConvInteger': [10],
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'ConvTranspose': [1, 11],
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'Cos': [7],
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'Cosh': [9],
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'CumSum': [11],
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'DepthToSpace': [1, 11],
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'DequantizeLinear': [10],
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'Det': [11],
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'DictVectorizer': [],
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'Div': [1, 6, 7],
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'Dropout': [1, 6, 7, 10],
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'DynamicQuantizeLinear': [11],
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'Einsum': [],
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'Elu': [1, 6],
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'Equal': [1, 7, 11],
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'Erf': [9],
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'Exp': [1, 6],
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'Expand': [8],
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'EyeLike': [9],
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'FeatureVectorizer': [],
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'Flatten': [1, 9, 11],
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'Floor': [1, 6],
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'GRU': [1, 3, 7],
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'Gather': [1, 11],
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'GatherElements': [11],
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'GatherND': [11],
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'Gemm': [1, 6, 7, 9, 11],
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'GlobalAveragePool': [1],
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'GlobalLpPool': [1, 2],
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'GlobalMaxPool': [1],
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'Gradient': [],
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'GraphCall': [],
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'Greater': [1, 7, 9],
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'GreaterOrEqual': [],
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'HardSigmoid': [1, 6],
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'Hardmax': [1, 11],
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'Identity': [1],
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'If': [1, 11],
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'ImageScaler': [1],
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'Imputer': [],
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'InstanceNormalization': [1, 6],
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'IsInf': [10],
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'IsNaN': [9],
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'LRN': [1],
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'LSTM': [1, 7],
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'LabelEncoder': [],
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'LeakyRelu': [1, 6],
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'Less': [1, 7, 9],
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'LessOrEqual': [],
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'LinearClassifier': [],
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'LinearRegressor': [],
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'Log': [1, 6],
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'LogSoftmax': [1, 11],
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'Loop': [1, 11],
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'LpNormalization': [1],
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'LpPool': [1, 2, 11],
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'MatMul': [1, 9],
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'MatMulInteger': [10],
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'Max': [1, 6, 8],
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'MaxPool': [1, 8, 10, 11, 12],
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'MaxRoiPool': [],
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'MaxUnpool': [9, 11],
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'Mean': [1, 6, 8],
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'MeanVarianceNormalization': [1, 9],
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'Min': [1, 6, 8],
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'Mod': [10],
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'Momentum': [],
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'Mul': [1, 6, 7],
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'Multinomial': [],
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'Neg': [1, 6],
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'NegativeLogLikelihoodLoss': [],
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'NonMaxSuppression': [10, 11],
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'NonZero': [9],
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'Normalizer': [],
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'Not': [1],
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'OneHot': [9, 11],
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'OneHotEncoder': [],
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'Or': [1, 7],
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'PRelu': [1, 6, 7, 9],
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'Pad': [1, 2, 11],
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'Pow': [1, 7],
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'QLinearConv': [10],
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'QLinearMatMul': [10],
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'QuantizeLinear': [10],
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'RNN': [1, 7],
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'RandomNormal': [1],
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'RandomNormalLike': [1],
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'RandomUniform': [1],
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'RandomUniformLike': [1],
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'Range': [11],
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'Reciprocal': [1, 6],
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'ReduceL1': [1, 11],
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'ReduceL2': [1, 11],
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'ReduceLogSum': [1, 11],
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'ReduceLogSumExp': [1, 11],
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'ReduceMax': [1, 11, 12],
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'ReduceMean': [1, 11],
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'ReduceMin': [1, 11, 12],
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'ReduceProd': [1, 11],
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'ReduceSum': [1, 11],
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'ReduceSumSquare': [1, 11],
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'Relu': [1, 6],
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'Reshape': [1, 5],
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'Resize': [10, 11],
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'ReverseSequence': [10],
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'RoiAlign': [],
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'Round': [11],
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'SVMClassifier': [],
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'SVMRegressor': [],
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'Scaler': [],
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'Scan': [8, 9, 11],
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'Scatter': [9],
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'ScatterElements': [11],
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'ScatterND': [11],
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'Selu': [1, 6],
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'SequenceAt': [11],
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'SequenceConstruct': [11],
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'SequenceEmpty': [11],
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'SequenceErase': [11],
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'SequenceInsert': [11],
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'SequenceLength': [11],
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'Shape': [1],
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'Shrink': [9],
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'Sigmoid': [1, 6],
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'Sign': [9],
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'Sin': [7],
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'Sinh': [9],
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'Size': [1],
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'Slice': [1, 10, 11],
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'Softmax': [1, 11],
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'SoftmaxCrossEntropyLoss': [],
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'Softplus': [1],
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'Softsign': [1],
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'SpaceToDepth': [1],
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'Split': [1, 2, 11],
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'SplitToSequence': [],
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'Sqrt': [1, 6],
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'Squeeze': [1, 11],
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'StringNormalizer': [],
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'Sub': [1, 6, 7],
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'Sum': [1, 6, 8],
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'Tan': [7],
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'Tanh': [1, 6],
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'TfIdfVectorizer': [9],
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'ThresholdedRelu': [1, 10],
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'Tile': [1, 6],
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'TopK': [1, 10, 11],
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'Transpose': [1],
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'TreeEnsembleClassifier': [],
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'TreeEnsembleRegressor': [],
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'Unique': [],
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'Unsqueeze': [1, 11],
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'Upsample': [7, 9],
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'Where': [9],
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'Xor': [1, 7],
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'ZipMap': []
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}
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backend_partial_support = {
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'Cast': 'Cast string to float32/float64/int32/int64 are not supported in '
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'Tensorflow.',
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'Clip': 'Clip input in uint64 is not supported in Tensorflow.',
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'ConvTranspose': 'ConvTranspose with dilations != 1, or transposed '
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'convolution for 4D or higher are not supported in '
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'Tensorflow.',
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'CumSum': 'CumSum inputs in uint32/uint64 are not supported in Tensorflow.',
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'Equal': 'Equal inputs in uint16/uint32/uint64 are not supported in '
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'Tensorflow.',
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'GRU': 'GRU with clip or GRU with linear_before_reset, or GRU not using '
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'sigmoid for z and r, or GRU using Elu as the activation function '
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'with alpha != 1, or GRU using HardSigmoid as the activation '
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'function with alpha != 0.2 or beta != 0.5 are not supported in '
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'TensorFlow.',
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'LSTM': 'LSTM not using sigmoid for `f`, or LSTM not using the same '
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'activation for `g` and `h` are not supported in Tensorflow.',
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'MaxPool': 'MaxPoolWithArgmax with pad is None or incompatible mode, or '
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'MaxPoolWithArgmax with 4D or higher input, orMaxPoolWithArgmax '
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'with column major are not supported in Tensorflow.',
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'Mod': 'Mod Dividend or Divisor in int8/int16/uint8/uint16/uint32/uint64 '
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'are not supported in Tensorflow.',
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'OneHot': 'OneHot indices in '
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'uint16/uint32/uint64/int8/int16/float16/float/double, or OneHot '
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'depth in '
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'uint8/uint16/uint32/uint64/int8/int16/int64/float16/float/double '
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'are not supported in Tensorflow.',
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'RNN': 'RNN with clip is not supported in Tensorflow.',
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'Resize': 'Resize required 4D input in Tensorflow. For opset 11, only the '
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'following attributes and inputs conbination are supported in '
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'Tensorflow:\n'
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'\t1. mode=nearest, '
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'coordinate_transformation_mode=align_corners, '
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'nearest_mode=round_prefer_ceil, can use scales(*) or sizes.\n'
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'\t2. mode=nearest, coordinate_transformation_mode=asymmetric, '
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'nearest_mode=floor, can use scales(*) or sizes.\n'
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'\t3. mode=nearest, '
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'coordinate_transformation_mode=tf_half_pixel_for_nn, '
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'nearest_mode=floor, can use scales(*) or sizes.\n'
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'\t4. mode=linear, coordinate_transformation_mode=align_corners, '
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'can use scales(*) or sizes.\n'
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'\t5. mode=linear, coordinate_transformation_mode=asymmetric, '
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'can use scales(*) or sizes.\n'
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'\t6. mode=linear, coordinate_transformation_mode=half_pixel, '
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'can use scales(*) or sizes.\n'
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'\t7. mode=cubic, coordinate_transformation_mode=align_corners, '
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'cubic_coeff_a=-0.5, exclude_outside=1, can use scales(*) or '
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'sizes.\n'
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'\t8. mode=cubic, coordinate_transformation_mode=asymmetric, '
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'cubic_coeff_a=-0.5, exclude_outside=1, can use scales(*) or '
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'sizes.\n'
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'\t9. mode=cubic, coordinate_transformation_mode=half_pixel, '
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'cubic_coeff_a=-0.5, exclude_outside=1, can use scales(*) or '
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'sizes.\n'
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'\t10. mode=nearest, '
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'coordinate_transformation_mode=tf_crop_and_resize, '
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'extrapolation_value=any_float_value, '
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'nearest_mode=round_prefer_ceil, can use scales or sizes.\n'
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'\t11. mode=linear, '
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'coordinate_transformation_mode=tf_crop_and_resize, '
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'extrapolation_value=any_float_value, can use scales or sizes.\n'
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'\t- Note (*): The accuracy of your model will go down, if the '
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'height and the width of the new sizes(scales * origial sizes) '
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'are not in whole numbers.',
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'Upsample': 'Upsample required 4D input in Tensorflow.'
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}
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