TensorFlow MRI 0.20.0

Release 0.20.0

Major Features and Improvements

• tfmri.layers:

  • Added new layers MaxPooling1D, MaxPooling2D, MaxPooling3D,
    AveragePooling1D, AveragePooling2D and AveragePooling3D.
    These are drop-in replacements for the core Keras layers of the same name,
    but they also support complex values.
  • Added new layers DWT1D, DWT2D, DWT3D, IDWT1D, IDWT2D,
    and IDWT3D to compute 1D, 2D and 3D forward and inverse discrete wavelet
    transforms.
  • Layer ConvBlock is now deprecated in favor of the new endpoints in
    the tfmri.models submodule.
  • Layer UNet is now deprecated in favor of the new endpoints in
    the tfmri.models submodule.

• tfmri.models:

  • Added new models ConvBlock1D, ConvBlock2D and ConvBlock3D. These
    replace the previous ConvBlock layer, which is now deprecated.
  • Added new models UNet1D, UNet2D and UNet3D. These replace
    the previous UNet layer, which is now deprecated.

Bug Fixes and Other Changes

• tfmri.signal:

  • Improved static shape inference for dwt op.