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array.py
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#######################################################
# Copyright (c) 2015, ArrayFire
# All rights reserved.
#
# This file is distributed under 3-clause BSD license.
# The complete license agreement can be obtained at:
# http://arrayfire.com/licenses/BSD-3-Clause
########################################################
"""
arrayfire.Array class and helper functions.
"""
import inspect
from .library import *
from .util import *
from .util import _is_number
from .bcast import _bcast_var
from .base import *
from .index import *
from .index import _Index4
def _create_array(buf, numdims, idims, dtype):
out_arr = ct.c_void_p(0)
c_dims = dim4(idims[0], idims[1], idims[2], idims[3])
safe_call(backend.get().af_create_array(ct.pointer(out_arr), ct.c_void_p(buf),
numdims, ct.pointer(c_dims), dtype.value))
return out_arr
def _create_empty_array(numdims, idims, dtype):
out_arr = ct.c_void_p(0)
c_dims = dim4(idims[0], idims[1], idims[2], idims[3])
safe_call(backend.get().af_create_handle(ct.pointer(out_arr),
numdims, ct.pointer(c_dims), dtype.value))
return out_arr
def constant_array(val, d0, d1=None, d2=None, d3=None, dtype=Dtype.f32):
"""
Internal function to create a C array. Should not be used externall.
"""
if not isinstance(dtype, ct.c_int):
if isinstance(dtype, int):
dtype = ct.c_int(dtype)
elif isinstance(dtype, Dtype):
dtype = ct.c_int(dtype.value)
else:
raise TypeError("Invalid dtype")
out = ct.c_void_p(0)
dims = dim4(d0, d1, d2, d3)
if isinstance(val, complex):
c_real = ct.c_double(val.real)
c_imag = ct.c_double(val.imag)
if (dtype.value != Dtype.c32.value and dtype.value != Dtype.c64.value):
dtype = Dtype.c32.value
safe_call(backend.get().af_constant_complex(ct.pointer(out), c_real, c_imag,
4, ct.pointer(dims), dtype))
elif dtype.value == Dtype.s64.value:
c_val = ct.c_longlong(val.real)
safe_call(backend.get().af_constant_long(ct.pointer(out), c_val, 4, ct.pointer(dims)))
elif dtype.value == Dtype.u64.value:
c_val = ct.c_ulonglong(val.real)
safe_call(backend.get().af_constant_ulong(ct.pointer(out), c_val, 4, ct.pointer(dims)))
else:
c_val = ct.c_double(val)
safe_call(backend.get().af_constant(ct.pointer(out), c_val, 4, ct.pointer(dims), dtype))
return out
def _binary_func(lhs, rhs, c_func):
out = Array()
other = rhs
if (_is_number(rhs)):
ldims = dim4_to_tuple(lhs.dims())
rty = implicit_dtype(rhs, lhs.type())
other = Array()
other.arr = constant_array(rhs, ldims[0], ldims[1], ldims[2], ldims[3], rty.value)
elif not isinstance(rhs, Array):
raise TypeError("Invalid parameter to binary function")
safe_call(c_func(ct.pointer(out.arr), lhs.arr, other.arr, _bcast_var.get()))
return out
def _binary_funcr(lhs, rhs, c_func):
out = Array()
other = lhs
if (_is_number(lhs)):
rdims = dim4_to_tuple(rhs.dims())
lty = implicit_dtype(lhs, rhs.type())
other = Array()
other.arr = constant_array(lhs, rdims[0], rdims[1], rdims[2], rdims[3], lty.value)
elif not isinstance(lhs, Array):
raise TypeError("Invalid parameter to binary function")
c_func(ct.pointer(out.arr), other.arr, rhs.arr, _bcast_var.get())
return out
def _ctype_to_lists(ctype_arr, dim, shape, offset=0):
if (dim == 0):
return list(ctype_arr[offset : offset + shape[0]])
else:
dim_len = shape[dim]
res = [[]] * dim_len
for n in range(dim_len):
res[n] = _ctype_to_lists(ctype_arr, dim - 1, shape, offset)
offset += shape[0]
return res
def _slice_to_length(key, dim):
tkey = [key.start, key.stop, key.step]
if tkey[0] is None:
tkey[0] = 0
elif tkey[0] < 0:
tkey[0] = dim - tkey[0]
if tkey[1] is None:
tkey[1] = dim
elif tkey[1] < 0:
tkey[1] = dim - tkey[1]
if tkey[2] is None:
tkey[2] = 1
return int(((tkey[1] - tkey[0] - 1) / tkey[2]) + 1)
def _get_info(dims, buf_len):
elements = 1
numdims = len(dims)
idims = [1]*4
for i in range(numdims):
elements *= dims[i]
idims[i] = dims[i]
if (elements == 0):
if (buf_len != 0):
idims = [buf_len, 1, 1, 1]
numdims = 1
else:
raise RuntimeError("Invalid size")
return numdims, idims
def _get_indices(key):
S = Index(slice(None))
inds = _Index4(S, S, S, S)
if isinstance(key, tuple):
n_idx = len(key)
for n in range(n_idx):
inds[n] = Index(key[n])
else:
inds[0] = Index(key)
return inds
def _get_assign_dims(key, idims):
dims = [1]*4
for n in range(len(idims)):
dims[n] = idims[n]
if _is_number(key):
dims[0] = 1
return dims
elif isinstance(key, slice):
dims[0] = _slice_to_length(key, idims[0])
return dims
elif isinstance(key, ParallelRange):
dims[0] = _slice_to_length(key.S, idims[0])
return dims
elif isinstance(key, BaseArray):
dims[0] = key.elements()
return dims
elif isinstance(key, tuple):
n_inds = len(key)
for n in range(n_inds):
if (_is_number(key[n])):
dims[n] = 1
elif (isinstance(key[n], BaseArray)):
dims[n] = key[n].elements()
elif (isinstance(key[n], slice)):
dims[n] = _slice_to_length(key[n], idims[n])
elif (isinstance(key[n], ParallelRange)):
dims[n] = _slice_to_length(key[n].S, idims[n])
else:
raise IndexError("Invalid type while assigning to arrayfire.array")
return dims
else:
raise IndexError("Invalid type while assigning to arrayfire.array")
def transpose(a, conj=False):
"""
Perform the transpose on an input.
Parameters
-----------
a : af.Array
Multi dimensional arrayfire array.
conj : optional: bool. default: False.
Flag to specify if a complex conjugate needs to applied for complex inputs.
Returns
--------
out : af.Array
Containing the tranpose of `a` for all batches.
"""
out = Array()
safe_call(backend.get().af_transpose(ct.pointer(out.arr), a.arr, conj))
return out
def transpose_inplace(a, conj=False):
"""
Perform inplace transpose on an input.
Parameters
-----------
a : af.Array
- Multi dimensional arrayfire array.
- Contains transposed values on exit.
conj : optional: bool. default: False.
Flag to specify if a complex conjugate needs to applied for complex inputs.
Note
-------
Input `a` needs to be a square matrix or a batch of square matrices.
"""
safe_call(backend.get().af_transpose_inplace(a.arr, conj))
class Array(BaseArray):
"""
A multi dimensional array container.
Parameters
----------
src : optional: array.array, list or C buffer. default: None.
- When `src` is `array.array` or `list`, the data is copied to create the Array()
- When `src` is None, an empty buffer is created.
dims : optional: tuple of ints. default: (0,)
- When using the default values of `dims`, the dims are caclulated as `len(src)`
dtype: optional: str or arrayfire.Dtype. default: None.
- if str, must be one of the following:
- 'f' for float
- 'd' for double
- 'b' for bool
- 'B' for unsigned char
- 'i' for signed 32 bit integer
- 'I' for unsigned 32 bit integer
- 'l' for signed 64 bit integer
- 'L' for unsigned 64 bit integer
- 'F' for 32 bit complex number
- 'D' for 64 bit complex number
- if arrayfire.Dtype, must be one of the following:
- Dtype.f32 for float
- Dtype.f64 for double
- Dtype.b8 for bool
- Dtype.u8 for unsigned char
- Dtype.s32 for signed 32 bit integer
- Dtype.u32 for unsigned 32 bit integer
- Dtype.s64 for signed 64 bit integer
- Dtype.u64 for unsigned 64 bit integer
- Dtype.c32 for 32 bit complex number
- Dtype.c64 for 64 bit complex number
- if None, Dtype.f32 is assumed
Attributes
-----------
arr: ctypes.c_void_p
ctypes variable containing af_array from arrayfire library.
Examples
--------
Creating an af.Array() from array.array()
>>> import arrayfire as af
>>> import array
>>> a = array.array('f', (1, 2, 3, 4))
>>> b = af.Array(a, (2,2))
>>> af.display(b)
[2 2 1 1]
1.0000 3.0000
2.0000 4.0000
Creating an af.Array() from a list
>>> import arrayfire as af
>>> import array
>>> a = [1, 2, 3, 4]
>>> b = af.Array(a)
>>> af.display(b)
[4 1 1 1]
1.0000
2.0000
3.0000
4.0000
Creating an af.Array() from numpy.array()
>>> import numpy as np
>>> import arrayfire as af
>>> a = np.random.random((2,2))
>>> a
array([[ 0.33042524, 0.36135449],
[ 0.86748649, 0.42199135]])
>>> b = af.Array(a.ctypes.data, a.shape, a.dtype.char)
>>> af.display(b)
[2 2 1 1]
0.3304 0.8675
0.3614 0.4220
Note
-----
- The class is currently limited to 4 dimensions.
- arrayfire.Array() uses column major format.
- numpy uses row major format by default which can cause issues during conversion
"""
def __init__(self, src=None, dims=(0,), dtype=None):
super(Array, self).__init__()
buf=None
buf_len=0
if dtype is not None:
if isinstance(dtype, str):
type_char = dtype
else:
type_char = to_typecode[dtype.value]
else:
type_char = None
_type_char='f'
backend.lock()
if src is not None:
if (isinstance(src, Array)):
safe_call(backend.get().af_retain_array(ct.pointer(self.arr), src.arr))
return
host = __import__("array")
if isinstance(src, host.array):
buf,buf_len = src.buffer_info()
_type_char = src.typecode
numdims, idims = _get_info(dims, buf_len)
elif isinstance(src, list):
tmp = host.array('f', src)
buf,buf_len = tmp.buffer_info()
_type_char = tmp.typecode
numdims, idims = _get_info(dims, buf_len)
elif isinstance(src, int) or isinstance(src, ct.c_void_p):
buf = src
numdims, idims = _get_info(dims, buf_len)
elements = 1
for dim in idims:
elements *= dim
if (elements == 0):
raise RuntimeError("Expected dims when src is data pointer")
if (type_char is None):
raise TypeError("Expected type_char when src is data pointer")
_type_char = type_char
else:
raise TypeError("src is an object of unsupported class")
if (type_char is not None and
type_char != _type_char):
raise TypeError("Can not create array of requested type from input data type")
self.arr = _create_array(buf, numdims, idims, to_dtype[_type_char])
else:
if type_char is None:
type_char = 'f'
numdims = len(dims)
idims = [1] * 4
for n in range(numdims):
idims[n] = dims[n]
self.arr = _create_empty_array(numdims, idims, to_dtype[type_char])
def copy(self):
"""
Performs a deep copy of the array.
Returns
-------
out: af.Array()
An identical copy of self.
"""
out = Array()
safe_call(backend.get().af_copy_array(ct.pointer(out.arr), self.arr))
return out
def __del__(self):
"""
Release the C array when going out of scope
"""
if self.arr.value:
backend.get().af_release_array(self.arr)
def device_ptr(self):
"""
Return the device pointer held by the array.
Returns
------
ptr : int
Contains location of the device pointer
Note
----
- This can be used to integrate with custom C code and / or PyCUDA or PyOpenCL.
- No mem copy is peformed, this function returns the raw device pointer.
"""
ptr = ct.c_void_p(0)
backend.get().af_get_device_ptr(ct.pointer(ptr), self.arr)
return ptr.value
def elements(self):
"""
Return the number of elements in the array.
"""
num = ct.c_ulonglong(0)
safe_call(backend.get().af_get_elements(ct.pointer(num), self.arr))
return num.value
def dtype(self):
"""
Return the data type as a arrayfire.Dtype enum value.
"""
dty = ct.c_int(Dtype.f32.value)
safe_call(backend.get().af_get_type(ct.pointer(dty), self.arr))
return to_dtype[typecodes[dty.value]]
def type(self):
"""
Return the data type as an int.
"""
return self.dtype().value
def dims(self):
"""
Return the shape of the array as a tuple.
"""
d0 = ct.c_longlong(0)
d1 = ct.c_longlong(0)
d2 = ct.c_longlong(0)
d3 = ct.c_longlong(0)
safe_call(backend.get().af_get_dims(ct.pointer(d0), ct.pointer(d1),
ct.pointer(d2), ct.pointer(d3), self.arr))
dims = (d0.value,d1.value,d2.value,d3.value)
return dims[:self.numdims()]
def numdims(self):
"""
Return the number of dimensions of the array.
"""
nd = ct.c_uint(0)
safe_call(backend.get().af_get_numdims(ct.pointer(nd), self.arr))
return nd.value
def is_empty(self):
"""
Check if the array is empty i.e. it has no elements.
"""
res = ct.c_bool(False)
safe_call(backend.get().af_is_empty(ct.pointer(res), self.arr))
return res.value
def is_scalar(self):
"""
Check if the array is scalar i.e. it has only one element.
"""
res = ct.c_bool(False)
safe_call(backend.get().af_is_scalar(ct.pointer(res), self.arr))
return res.value
def is_row(self):
"""
Check if the array is a row i.e. it has a shape of (1, cols).
"""
res = ct.c_bool(False)
safe_call(backend.get().af_is_row(ct.pointer(res), self.arr))
return res.value
def is_column(self):
"""
Check if the array is a column i.e. it has a shape of (rows, 1).
"""
res = ct.c_bool(False)
safe_call(backend.get().af_is_column(ct.pointer(res), self.arr))
return res.value
def is_vector(self):
"""
Check if the array is a vector i.e. it has a shape of one of the following:
- (rows, 1)
- (1, cols)
- (1, 1, vols)
- (1, 1, 1, batch)
"""
res = ct.c_bool(False)
safe_call(backend.get().af_is_vector(ct.pointer(res), self.arr))
return res.value
def is_complex(self):
"""
Check if the array is of complex type.
"""
res = ct.c_bool(False)
safe_call(backend.get().af_is_complex(ct.pointer(res), self.arr))
return res.value
def is_real(self):
"""
Check if the array is not of complex type.
"""
res = ct.c_bool(False)
safe_call(backend.get().af_is_real(ct.pointer(res), self.arr))
return res.value
def is_double(self):
"""
Check if the array is of double precision floating point type.
"""
res = ct.c_bool(False)
safe_call(backend.get().af_is_double(ct.pointer(res), self.arr))
return res.value
def is_single(self):
"""
Check if the array is of single precision floating point type.
"""
res = ct.c_bool(False)
safe_call(backend.get().af_is_single(ct.pointer(res), self.arr))
return res.value
def is_real_floating(self):
"""
Check if the array is real and of floating point type.
"""
res = ct.c_bool(False)
safe_call(backend.get().af_is_realfloating(ct.pointer(res), self.arr))
return res.value
def is_floating(self):
"""
Check if the array is of floating point type.
"""
res = ct.c_bool(False)
safe_call(backend.get().af_is_floating(ct.pointer(res), self.arr))
return res.value
def is_integer(self):
"""
Check if the array is of integer type.
"""
res = ct.c_bool(False)
safe_call(backend.get().af_is_integer(ct.pointer(res), self.arr))
return res.value
def is_bool(self):
"""
Check if the array is of type b8.
"""
res = ct.c_bool(False)
safe_call(backend.get().af_is_bool(ct.pointer(res), self.arr))
return res.value
def __add__(self, other):
"""
Return self + other.
"""
return _binary_func(self, other, backend.get().af_add)
def __iadd__(self, other):
"""
Perform self += other.
"""
self = _binary_func(self, other, backend.get().af_add)
return self
def __radd__(self, other):
"""
Return other + self.
"""
return _binary_funcr(other, self, backend.get().af_add)
def __sub__(self, other):
"""
Return self - other.
"""
return _binary_func(self, other, backend.get().af_sub)
def __isub__(self, other):
"""
Perform self -= other.
"""
self = _binary_func(self, other, backend.get().af_sub)
return self
def __rsub__(self, other):
"""
Return other - self.
"""
return _binary_funcr(other, self, backend.get().af_sub)
def __mul__(self, other):
"""
Return self * other.
"""
return _binary_func(self, other, backend.get().af_mul)
def __imul__(self, other):
"""
Perform self *= other.
"""
self = _binary_func(self, other, backend.get().af_mul)
return self
def __rmul__(self, other):
"""
Return other * self.
"""
return _binary_funcr(other, self, backend.get().af_mul)
def __truediv__(self, other):
"""
Return self / other.
"""
return _binary_func(self, other, backend.get().af_div)
def __itruediv__(self, other):
"""
Perform self /= other.
"""
self = _binary_func(self, other, backend.get().af_div)
return self
def __rtruediv__(self, other):
"""
Return other / self.
"""
return _binary_funcr(other, self, backend.get().af_div)
def __div__(self, other):
"""
Return self / other.
"""
return _binary_func(self, other, backend.get().af_div)
def __idiv__(self, other):
"""
Perform other / self.
"""
self = _binary_func(self, other, backend.get().af_div)
return self
def __rdiv__(self, other):
"""
Return other / self.
"""
return _binary_funcr(other, self, backend.get().af_div)
def __mod__(self, other):
"""
Return self % other.
"""
return _binary_func(self, other, backend.get().af_mod)
def __imod__(self, other):
"""
Perform self %= other.
"""
self = _binary_func(self, other, backend.get().af_mod)
return self
def __rmod__(self, other):
"""
Return other % self.
"""
return _binary_funcr(other, self, backend.get().af_mod)
def __pow__(self, other):
"""
Return self ** other.
"""
return _binary_func(self, other, backend.get().af_pow)
def __ipow__(self, other):
"""
Perform self **= other.
"""
self = _binary_func(self, other, backend.get().af_pow)
return self
def __rpow__(self, other):
"""
Return other ** self.
"""
return _binary_funcr(other, self, backend.get().af_pow)
def __lt__(self, other):
"""
Return self < other.
"""
return _binary_func(self, other, backend.get().af_lt)
def __gt__(self, other):
"""
Return self > other.
"""
return _binary_func(self, other, backend.get().af_gt)
def __le__(self, other):
"""
Return self <= other.
"""
return _binary_func(self, other, backend.get().af_le)
def __ge__(self, other):
"""
Return self >= other.
"""
return _binary_func(self, other, backend.get().af_ge)
def __eq__(self, other):
"""
Return self == other.
"""
return _binary_func(self, other, backend.get().af_eq)
def __ne__(self, other):
"""
Return self != other.
"""
return _binary_func(self, other, backend.get().af_neq)
def __and__(self, other):
"""
Return self & other.
"""
return _binary_func(self, other, backend.get().af_bitand)
def __iand__(self, other):
"""
Perform self &= other.
"""
self = _binary_func(self, other, backend.get().af_bitand)
return self
def __or__(self, other):
"""
Return self | other.
"""
return _binary_func(self, other, backend.get().af_bitor)
def __ior__(self, other):
"""
Perform self |= other.
"""
self = _binary_func(self, other, backend.get().af_bitor)
return self
def __xor__(self, other):
"""
Return self ^ other.
"""
return _binary_func(self, other, backend.get().af_bitxor)
def __ixor__(self, other):
"""
Perform self ^= other.
"""
self = _binary_func(self, other, backend.get().af_bitxor)
return self
def __lshift__(self, other):
"""
Return self << other.
"""
return _binary_func(self, other, backend.get().af_bitshiftl)
def __ilshift__(self, other):
"""
Perform self <<= other.
"""
self = _binary_func(self, other, backend.get().af_bitshiftl)
return self
def __rshift__(self, other):
"""
Return self >> other.
"""
return _binary_func(self, other, backend.get().af_bitshiftr)
def __irshift__(self, other):
"""
Perform self >>= other.
"""
self = _binary_func(self, other, backend.get().af_bitshiftr)
return self
def __neg__(self):
"""
Return -self
"""
return 0 - self
def __pos__(self):
"""
Return +self
"""
return self
def __invert__(self):
"""
Return ~self
"""
return self == 0
def __nonzero__(self):
return self != 0
# TODO:
# def __abs__(self):
# return self
def __getitem__(self, key):
"""
Return self[key]
Note
----
Ellipsis not supported as key
"""
try:
out = Array()
n_dims = self.numdims()
inds = _get_indices(key)
safe_call(backend.get().af_index_gen(ct.pointer(out.arr),
self.arr, ct.c_longlong(n_dims), inds.pointer))
return out
except RuntimeError as e:
raise IndexError(str(e))
def __setitem__(self, key, val):
"""
Perform self[key] = val
Note
----
Ellipsis not supported as key
"""
try:
n_dims = self.numdims()
if (_is_number(val)):
tdims = _get_assign_dims(key, self.dims())
other_arr = constant_array(val, tdims[0], tdims[1], tdims[2], tdims[3], self.type())
del_other = True
else:
other_arr = val.arr
del_other = False
out_arr = ct.c_void_p(0)
inds = _get_indices(key)
safe_call(backend.get().af_assign_gen(ct.pointer(out_arr),
self.arr, ct.c_longlong(n_dims), inds.pointer,
other_arr))
safe_call(backend.get().af_release_array(self.arr))
if del_other:
safe_call(backend.get().af_release_array(other_arr))
self.arr = out_arr
except RuntimeError as e:
raise IndexError(str(e))
def to_ctype(self, row_major=False, return_shape=False):
"""
Return the data as a ctype C array after copying to host memory
Parameters
---------
row_major: optional: bool. default: False.
Specifies if a transpose needs to occur before copying to host memory.
return_shape: optional: bool. default: False.
Specifies if the shape of the array needs to be returned.
Returns
-------
If return_shape is False:
res: The ctypes array of the appropriate type and length.
else :
(res, dims): tuple of the ctypes array and the shape of the array
"""
if (self.arr.value == 0):
raise RuntimeError("Can not call to_ctype on empty array")
tmp = transpose(self) if row_major else self
ctype_type = to_c_type[self.type()] * self.elements()
res = ctype_type()
safe_call(backend.get().af_get_data_ptr(ct.pointer(res), self.arr))
if (return_shape):
return res, self.dims()
else:
return res
def to_array(self, row_major=False, return_shape=False):
"""
Return the data as array.array
Parameters
---------
row_major: optional: bool. default: False.
Specifies if a transpose needs to occur before copying to host memory.
return_shape: optional: bool. default: False.
Specifies if the shape of the array needs to be returned.
Returns
-------
If return_shape is False:
res: array.array of the appropriate type and length.
else :
(res, dims): array.array and the shape of the array
"""
if (self.arr.value == 0):
raise RuntimeError("Can not call to_array on empty array")
res = self.to_ctype(row_major, return_shape)
host = __import__("array")
h_type = to_typecode[self.type()]
if (return_shape):
return host.array(h_type, res[0]), res[1]
else:
return host.array(h_type, res)
def to_list(self, row_major=False):
"""
Return the data as list
Parameters
---------
row_major: optional: bool. default: False.
Specifies if a transpose needs to occur before copying to host memory.
return_shape: optional: bool. default: False.
Specifies if the shape of the array needs to be returned.
Returns
-------