1 write to Inputs
Microsoft.ML.TensorFlow (1)
TensorflowTransform.cs (1)
301
Inputs
= inputColumnNames;
16 references to Inputs
Microsoft.ML.TensorFlow (16)
TensorflowTransform.cs (16)
306
(TFInputTypes, TFInputShapes, TFInputOperations) = GetInputInfo(Host, Session,
Inputs
, batchSize);
308
TFInputNodes = new TF_Output[
Inputs
.Length];
495
Host.AssertNonEmpty(
Inputs
);
496
ctx.Writer.Write(
Inputs
.Length);
497
foreach (var colName in
Inputs
)
547
_inputColIndices = new int[_parent.
Inputs
.Length];
548
_isInputVector = new bool[_parent.
Inputs
.Length];
549
_fullySpecifiedShapes = new TensorShape[_parent.
Inputs
.Length];
550
for (int i = 0; i < _parent.
Inputs
.Length; i++)
552
if (!inputSchema.TryGetColumnIndex(_parent.
Inputs
[i], out _inputColIndices[i]))
553
throw Host.ExceptSchemaMismatch(nameof(InputSchema), "source", _parent.
Inputs
[i]);
562
throw Host.ExceptSchemaMismatch(nameof(inputSchema), "input", _parent.
Inputs
[i], expectedType.ToString(), type.ToString());
597
throw Contracts.Except($"Input shape mismatch: Input '{_parent.
Inputs
[i]}' has shape {originalShape.ToString()}, but input data is of length {typeValueCount}.");
616
throw Contracts.Except($"Input shape mismatch: Input '{_parent.
Inputs
[i]}' has shape {originalShape.ToString()}, but input data is of length {typeValueCount}.");
756
Runner runner = new Runner(_parent.Session, _parent.
Inputs
.ToArray(), _parent.Outputs.ToArray());
759
for (int i = 0; i < _parent.
Inputs
.Length; i++)