{"record":{"id":"48adb8f6ecd7f3ee","repo":"jax-ml/jax","slug":"type-argument-of-array-view-is-not-supported","errorCode":null,"errorMessage":"`type` argument of array.view() is not supported.","messagePattern":"`type` argument of array\\.view\\(\\) is not supported\\.","errorType":"exception","errorClass":"NotImplementedError","httpStatus":null,"severity":"error","filePath":"jax/_src/numpy/array_methods.py","lineNumber":591,"sourceCode":"  However, there are no guarantees about the results of any expression involving\n  a view such as this: ``jnp.array([1, 2, 3], dtype=jnp.int8).view(jnp.bool_)``.\n  In particular, the results may change between JAX releases and depending on\n  the platform. To safely convert such an array to a boolean array, compare it\n  with `0`::\n\n    >>> jnp.array([1, 2, 0], dtype=jnp.int8) != 0\n    Array([ True,  True, False], dtype=bool)\n\n  Args:\n    dtype: An optional output dtype. If not specified, the output dtype is the\n      same as the input dtype.\n    type: Not implemented; accepted for NumPy compatibility.\n  Returns:\n    The array, viewed as the new dtype. Unlike NumPy, the array may or may not\n    be a copy of the input array.\n  \"\"\"\n  if type is not None:\n    raise NotImplementedError(\"`type` argument of array.view() is not supported.\")\n\n  if dtype is None:\n    return self\n\n  dtype = dtypes.check_and_canonicalize_user_dtype(dtype, \"view\")\n\n  nbits_in = dtypes.itemsize_bits(self.dtype)\n  nbits_out = dtypes.itemsize_bits(dtype)\n\n  if self.ndim == 0:\n    if nbits_in != nbits_out:\n      raise ValueError(\"view() of a 0d array is only supported if the itemsize is unchanged.\")\n    return _view(lax.expand_dims(self, (0,)), dtype).squeeze()\n\n  if (self.shape[-1] * nbits_in) % nbits_out != 0:\n    raise ValueError(\"When changing to a larger dtype, its size must be a divisor \"\n                     \"of the total size in bytes of the last axis of the array.\")\n","sourceCodeStart":573,"sourceCodeEnd":609,"githubUrl":"https://github.com/jax-ml/jax/blob/1e1c6a8fc06dfcd1247076ec5cae4640cea5d7bb/jax/_src/numpy/array_methods.py#L573-L609","documentation":"NumPy's ndarray.view accepts a `type` argument (Python buffer/exposed type) for object views; JAX arrays are not buffers and only support dtype-based views, so any non-None type raises NotImplementedError. Only dtype=None or a dtype is accepted.","triggerScenarios":"Calling `arr.view(type=some_type)` with type not None, e.g. `arr.view(type=np.ndarray)` or legacy code using view(type=...).","commonSituations":"Old NumPy code or tutorials using the three-argument form of view; interop wrappers that forward **kwargs to view.","solutions":["Remove the type argument and pass a dtype instead: arr.view(jnp.float32)","If a zero-copy buffer is needed, use np.asarray(jax_array) first and call view on the NumPy array"],"exampleFix":"# before\narr.view(type=np.uint8)\n\n# after\narr.view(jnp.uint8)","handlingStrategy":"validation","validationCode":"def view(a, dtype=None, type=None):\n    if type is not None:\n        raise TypeError('JAX view() does not accept type=')\n    return a.view(dtype)","typeGuard":null,"tryCatchPattern":null,"preventionTips":["Only pass dtype to view() in JAX","Drop the type kwarg when porting NumPy snippets"],"tags":["jax","view","not-implemented","numpy-compat"],"backgroundTag":"unsupported-argument-value","analyzedSha":"1e1c6a8fc06dfcd1247076ec5cae4640cea5d7bb","analyzedAt":"2026-08-27T09:53:25.647Z","schemaVersion":2},"datasetVersion":"2026-08-27T13:17:12.746Z"}