add: frombuffer to ivy functional api

ivy/container/creation.py

@@ -1320,3 +1320,163 @@ def one_hot(
             map_sequences=map_sequences,
             out=out,
         )
+
+    @staticmethod
+    def static_frombuffer(
+        buffer: ivy.Container,
+        dtype: Optional[Union[ivy.Dtype, ivy.NativeDtype]] = float,
+        count: Optional[int] = -1,
+        offset: Optional[int] = 0,
+        key_chains: Optional[Union[List[str], Dict[str, str]]] = None,
+        to_apply: bool = True,
+        prune_unapplied: bool = False,
+        map_sequences: bool = False,
+    ) -> ivy.Container:
+        """
+        ivy.Container static method variant of ivy.frombuffer. This method simply
+        wraps the function, and so the docstring for ivy.frombuffer also applies
+        to this method with minimal changes.
+
+        Parameters
+        ----------
+        buffer
+            An object that exposes the buffer interface.
+        dtype
+            Data-type of the returned array; default: float.
+        count
+            Number of items to read. -1 means all data in the buffer.
+        offset
+            Start reading the buffer from this offset (in bytes); default: 0.
+        key_chains
+            The key-chains to apply or not apply the method to. Default is ``None``.
+        to_apply
+            If True, the method will be applied to key_chains, otherwise key_chains will
+            be skipped. Default is ``True``.
+        prune_unapplied
+            Whether to prune key_chains for which the function was not applied. Default
+            is False.
+        map_sequences
+            Whether to also map method to sequences (lists, tuples).
+            Default is ``False``.
+
+        Returns
+        -------
+        out
+            1-dimensional array.
+
+        Examples
+        --------
+        With :class:`ivy.Container` inputs:
+
+        >>> x = ivy.Container(
+        ...     a = b'\x00\x00\x00\x00\x00\x00\xf0?\x00\x00\x00\x00\x00\x00\x00@',
+        ...     b = b'\x00\x00\x00\x00\x00\x00\x00@\x00\x00\x00\x00\x00\x00\xf0?\x00\x00\x00\x00\x00\x00\x00@'
+        ... )
+        >>> y = ivy.Container.static_frombuffer(x)
+        >>> print(y)
+        {
+            a: ivy.array([1., 2.]),
+            b: ivy.array([2., 1., 2.])
+        }
+
+        >>> x = ivy.Container(
+        ...     a = b'\x01\x02\x03\x04',
+        ...     b = b'\x05\x04\x03\x03\x02'
+        ... )
+        >>> y = ivy.Container.static_frombuffer(x, dtype=ivy.int8, count=3, offset=1)
+        >>> print(y)
+        {
+            a: ivy.array([2, 3, 4]),
+            b: ivy.array([4, 3, 3])
+        }
+        """
+        return ContainerBase.cont_multi_map_in_function(
+            "frombuffer",
+            buffer,
+            dtype=dtype,
+            count=count,
+            offset=offset,
+            key_chains=key_chains,
+            to_apply=to_apply,
+            prune_unapplied=prune_unapplied,
+            map_sequences=map_sequences,
+        )
+
+    def frombuffer(
+        self: ivy.Container,
+        dtype: Optional[Union[ivy.Dtype, ivy.NativeDtype]] = float,
+        count: Optional[int] = -1,
+        offset: Optional[int] = 0,
+        key_chains: Optional[Union[List[str], Dict[str, str]]] = None,
+        to_apply: bool = True,
+        prune_unapplied: bool = False,
+        map_sequences: bool = False,
+    ) -> ivy.Container:
+        """
+        ivy.Container instance method variant of ivy.frombuffer. This method
+        simply wraps the function, and so the docstring for ivy.frombuffer
+        also applies to this method with minimal changes.
+
+        Parameters
+        ----------
+        self
+            An object that exposes the buffer interface.
+        dtype
+            Data-type of the returned array; default: float.
+        count
+            Number of items to read. -1 means all data in the buffer.
+        offset
+            Start reading the buffer from this offset (in bytes); default: 0.
+        key_chains
+            The key-chains to apply or not apply the method to. Default is ``None``.
+        to_apply
+            If True, the method will be applied to key_chains, otherwise key_chains will
+            be skipped. Default is ``True``.
+        prune_unapplied
+            Whether to prune key_chains for which the function was not applied. Default
+            is False.
+        map_sequences
+            Whether to also map method to sequences (lists, tuples).
+            Default is ``False``.
+
+        Returns
+        -------
+        out
+            1-dimensional array.
+
+        Examples
+        --------
+        With :class:`ivy.Container` inputs:
+
+        >>> x = ivy.Container(
+        ...     a = b'\x00\x00\x00\x00\x00\x00\xf0?\x00\x00\x00\x00\x00\x00\x00@',
+        ...     b = b'\x00\x00\x00\x00\x00\x00\x00@\x00\x00\x00\x00\x00\x00\xf0?\x00\x00\x00\x00\x00\x00\x00@'
+        ... )
+        >>> y = ivy.frombuffer(x)
+        >>> print(y)
+        {
+            a: ivy.array([1., 2.]),
+            b: ivy.array([2., 1., 2.])
+        }
+
+        >>> x = ivy.Container(
+        ...     a = b'\x01\x02\x03\x04',
+        ...     b = b'\x05\x04\x03\x03\x02'
+        ... )
+        >>> y = ivy.frombuffer(x, dtype=ivy.int8, count=3, offset=1)
+        >>> print(y)
+        {
+            a: ivy.array([2, 3, 4]),
+            b: ivy.array([4, 3, 3])
+        }
+        """
+        return self.static_frombuffer(
+            self,
+            dtype=dtype,
+            count=count,
+            offset=offset,
+            key_chains=key_chains,
+            to_apply=to_apply,
+            prune_unapplied=prune_unapplied,
+            map_sequences=map_sequences,
+        )

ivy/functional/backends/jax/creation.py

@@ -340,3 +340,12 @@ def one_hot(
         res = jnp.moveaxis(res, -1, axis)
 
     return _to_device(res, device)
+
+
+def frombuffer(
+    buffer: bytes,
+    dtype: Optional[jnp.dtype] = float,
+    count: Optional[int] = -1,
+    offset: Optional[int] = 0,
+) -> JaxArray:
+    return jnp.frombuffer(buffer, dtype=dtype, count=count, offset=offset)

ivy/functional/backends/numpy/creation.py

@@ -273,3 +273,15 @@ def one_hot(
         res = np.moveaxis(res, -1, axis)
 
     return res
+
+
+def frombuffer(
+    buffer: bytes,
+    dtype: Optional[np.dtype] = float,
+    count: Optional[int] = -1,
+    offset: Optional[int] = 0,
+) -> np.ndarray:
+    if isinstance(dtype, list):
+        dtype = np.dtype(dtype[0])
+
+    return np.frombuffer(buffer, dtype=dtype, count=count, offset=offset)

ivy/functional/backends/tensorflow/creation.py

@@ -421,3 +421,22 @@ def one_hot(
     return tf.one_hot(
         indices, depth, on_value=on_value, off_value=off_value, axis=axis, dtype=dtype
     )
+
+
+@with_unsupported_dtypes({"1.11.0 and below": ("uint32", "uint64")}, backend_version)
+def frombuffer(
+    buffer: bytes,
+    dtype: Optional[tf.DType] = float,
+    count: Optional[int] = -1,
+    offset: Optional[int] = 0,
+) -> Union[tf.Tensor, tf.Variable]:
+    ret = tf.io.decode_raw(buffer, dtype)
+    dtype = tf.dtypes.as_dtype(dtype)
+    if offset > 0:
+        offset = int(offset / dtype.size)
+    if count > -1:
+        ret = ret[offset:offset + count]
+    else:
+        ret = ret[offset:]
+
+    return ret

ivy/functional/backends/torch/creation.py

@@ -611,3 +611,14 @@ def one_hot(
         res = torch.moveaxis(res, -1, axis)
 
     return res.to(device, dtype)
+
+
+def frombuffer(
+    buffer: bytes,
+    dtype: Optional[torch.dtype] = float,
+    count: Optional[int] = -1,
+    offset: Optional[int] = 0,
+) -> torch.Tensor:
+    dtype = ivy.as_native_dtype(dtype)
+
+    return torch.frombuffer(buffer, dtype=dtype, count=count, offset=offset)

ivy/functional/ivy/creation.py

@@ -1920,3 +1920,62 @@ def logspace(
         device=device,
         out=out,
     )
+
+
+@outputs_to_ivy_arrays
+@handle_nestable
+def frombuffer(
+    buffer: bytes,
+    dtype: Optional[Union[ivy.Dtype, ivy.NativeDtype]] = float,
+    count: Optional[int] = -1,
+    offset: Optional[int] = 0,
+) -> ivy.Array:
+    """
+    Interpret a buffer as a 1-dimensional array.
+
+    .. note::
+        Note that either of the following must be true:
+        1. count is a positive non-zero number, and the total number of bytes in the buffer is equal or greater than offset plus count times the size (in bytes) of dtype.
+        2. count is negative, and the length (number of bytes) of the buffer subtracted by the offset is a multiple of the size (in bytes) of dtype.
+
+    Parameters
+    ----------
+    buffer
+        An object that exposes the buffer interface.
+    dtype
+        Data-type of the returned array; default: float.
+    count
+        Number of items to read. -1 means all data in the buffer.
+    offset
+        Start reading the buffer from this offset (in bytes); default: 0.
+
+    Returns
+    -------
+    out
+        1-dimensional array.
+
+    Examples
+    --------
+    With :class:`bytes` inputs:
+
+    >>> x = b'\x00\x00\x00\x00\x00\x00\xf0?\x00\x00\x00\x00\x00\x00\x00@'
+    >>> y = ivy.frombuffer(x)
+    >>> print(y)
+    (ivy.array([1., 2.]))
+
+    >>> x = b'\x01\x02\x03\x04'
+    >>> y = ivy.frombuffer(x, dtype='int8', count=-2, offset=1)
+    >>> print(y)
+    (ivy.array([2, 3, 4]))
+
+    >>> x = b'\x00\x00\x80?\x00\x00\x00@\x00\x00@@\x00\x00\x80@\x00\x00\xa0@\x00\x00\xc0@'
+    >>> y = ivy.frombuffer(x, dtype='float32', count=4, offset=4)
+    >>> print(y)
+    (ivy.array([2., 3., 4., 5.]))
+    """
+    return current_backend().frombuffer(
+        buffer,
+        dtype=dtype,
+        count=count,
+        offset=offset,
+    )