tensorflow 2.7.0

• Default Tensorflow version installed by install_tensorflow() updated to 2.7

• Breaking changes:

  • shape() now returns a tf.TensorShape() object
    (Previously an R-list of NULLs or integers).
  • [ method for tf.TensorShape() objects also now returns a tf.TensorShape().
    Use [[, as.numeric, as.integer, and/or as.list to convert to R objects.
  • length() method for tensorflow.tensor now returns NA_integer_ for
    tensors with not fully defined shapes. (previously a zero length integer vector).
  • dim() method for tensorflow.tensor now returns an R integer vector
    with NA for dimensions that are undefined.
    (previously an R list with NULL for undefined dimension)

• New S3 generics for tf.TensorShape()'s:
  c, length, [<-, [[<-, merge, ==, !=, as_tensor(),
  as.list, as.integer, as.numeric, as.double, py_str
  (joining previous generics [ and [[).
  See ?shape for extended examples.

• Ops S3 generics for tensorflow.tensors that take two arguments now
  automatically cast a supplied non-tensor to the dtype of the supplied tensor
  that triggered the S3 dispatch. Casting is done via as_tensor().
  e.g., this now works:

  as_tensor(5L) - 2     # now returns tf.Tensor(3, shape=(), dtype=int32)
  

  previously it would raise an error:

  TypeError: `x` and `y` must have the same dtype, got tf.int32 != tf.float32
  

  Generics that now do autocasting:
  +, -, *, /, %/%, %%, ^, &, |, ==, !=, <, <=, >, >=

• install_tensorflow(): new argument with default pip_ignore_installed = TRUE.
  This ensures that all Tensorflow dependencies like Numpy are installed by pip
  rather than conda.

• A message with the Tensorflow version is now shown when the
  python module is loaded, e.g: "Loaded Tensorflow version 2.6.0"