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SOTA
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Accelerator Toolkit
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Deep Learning Toolkit
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- Exp
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- Add
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- RelativePositionBias
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- SparseToDenseMatMul
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- Attention
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- AdditiveAttention
- Attention
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- AdditiveAttention
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- MultiHeadAttention
- LSTM
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- SeparableConv1D
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- RNN (GRU)
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- 1D
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- AdditiveAttention
- Attention
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- Conv1D
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- GRU
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- LSTM
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- PReLU 2D
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- Resume
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- Dense
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- AdditiveAttention
- Attention
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- Conv1D
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- Conv1DTranspose
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- DepthwiseConv2D
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- BatchNormalization
- LayerNormalization
- PReLU 2D
- PReLU 3D
- PReLU 4D
- PReLU 5D
- Bidirectional
- GRU
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- RNN (GRU)
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- SimpleRNN
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- Dense
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- Conv1D
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- LayerNormalization
- PReLU 2D
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- GRU
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- SimpleRNN
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- Accuracy
- BinaryAccuracy
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- Hinge
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- Mean
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- MeanTensor
- OneHotIoU
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- Poisson
- Precision
- PrecisionAtRecall
- Recall
- RecallAtPrecision
- RootMeanSquaredError
- SensitivityAtSpecificity
- SparseCategoricalAccuracy
- SparseCategoricalCrossentropy
- SparseTopKCategoricalAccuracy
- Specificity
- SpecificityAtSensitivity
- SquaredHinge
- Sum
- TopKCategoricalAccuracy
- TrueNegatives
- TruePositives
- Resume
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- Dense
- Embedding
- AdditiveAttention
- Attention
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- Conv2DTranspose
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- DepthwiseConv2D
- SeparableConv1D
- SeparableConv2D
- BatchNormalization
- LayerNormalization
- PReLU 2D
- PReLU 3D
- PReLU 4D
- PReLU 5D
- Bidirectional
- GRU
- LSTM
- RNN (GRU)
- RNN (LSTM)
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- SimpleRNN
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- Dense
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- AdditiveAttention
- Attention
- MultiHeadAttention
- Conv1D
- Conv2D
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- ConvLSTM2D
- ConvLSTM3D
- Conv1DTranspose
- Conv2DTranspose
- Conv3DTranspose
- DepthwiseConv2D
- SeparableConv1D
- SeparableConv2D
- LayerNormalization
- PReLU 2D
- PReLU 3D
- PReLU 4D
- PReLU 5D
- Bidirectional
- GRU
- LSTM
- RNN (GRU)
- RNN (LSTM)
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- SimpleRNN
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Computer Vision Toolkit
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CUDA Toolkit
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- Resume
- Array size
- Index Array
- Replace Subset
- Insert Into Array
- Delete From Array
- Initialize Array
- Build Array
- Concatenate Array
- Array Subset
- Min & Max
- Reshape Array
- Short Array
- Reverse 1D array
- Shuffle array
- Search In Array
- Split 1D Array
- Split 2D Array
- Rotate 1D Array
- Increment Array Element
- Decrement Array Element
- Interpolate 1D Array
- Threshold 1D Array
- Interleave 1D Array
- Decimate 1D Array
- Transpose Array
- Remove Duplicate From 1D Array
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- Resume
- Add
- Substract
- Multiply
- Divide
- Quotient & Remainder
- Increment
- Decrement
- Add Array Element
- Multiply Array Element
- Absolute
- Round To Nearest
- Round Toward -Infinity
- Round Toward +Infinity
- Scale By Power Of Two
- Square Root
- Square
- Negate
- Reciprocal
- Sign
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Updated
Get File Info
Description
Obtains information regarding the contents of the file. This information is supplied for standard file formats only : BMP, TIFF, JPEG, JPEG2000, PNG, or AIPD. Type : polymorphic.
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Input parameters
File Path : path, file path (BMP, TIFF, JPEG, JPEG2000, PNG, AIPD).
Output parameters
Β File Type :Β string,Β file extension.
Β File Info : cluster,Β
Β Width :Β integer,Β image width.
Β Height :Β integer,Β image height.
Β Image Type :Β integer,Β specifies the type of the image.
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- Grayscale (U8) :Β 8 bits per pixel (unsigned, standard monochrome)
- Grayscale (I16) :Β 16 bits per pixel (signed)
- Grayscale (SGL) :Β 32 bits per pixel (floating point)
- Complex (CSG) :Β 2Β ΓΒ 32 bits per pixel (floating point)
- RGB (U32) :Β 32 bits per pixel (red, green, blue, alpha)
- HSL (U32) :Β 32 bits per pixel (hue, saturation, luminance, alpha)
- RGB (U64) :Β 64 bits per pixel (red, green, blue, alpha)
- Grayscale (U16) :Β 16 bits per pixel (unsigned)
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Examples
All these examples are snippets PNG, you can drop these Snippet onto the block diagram and get the depicted code added to your VI (Do not forget to install Computer Vision βlibrary to run it).
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