Python ctypes.c_longlong() Examples
The following are 30
code examples of ctypes.c_longlong().
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and go to the original project or source file by following the links above each example.
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ctypes
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Example #1
| Source File: _internal.py From twitter-stock-recommendation with MIT License | 6 votes |
|
def _getintp_ctype():
val = _getintp_ctype.cache
if val is not None:
return val
if ctypes is None:
import numpy as np
val = dummy_ctype(np.intp)
else:
char = dtype('p').char
if (char == 'i'):
val = ctypes.c_int
elif char == 'l':
val = ctypes.c_long
elif char == 'q':
val = ctypes.c_longlong
else:
val = ctypes.c_long
_getintp_ctype.cache = val
return val
Example #2
| Source File: _internal.py From predictive-maintenance-using-machine-learning with Apache License 2.0 | 6 votes |
|
def _getintp_ctype():
val = _getintp_ctype.cache
if val is not None:
return val
if ctypes is None:
import numpy as np
val = dummy_ctype(np.intp)
else:
char = dtype('p').char
if (char == 'i'):
val = ctypes.c_int
elif char == 'l':
val = ctypes.c_long
elif char == 'q':
val = ctypes.c_longlong
else:
val = ctypes.c_long
_getintp_ctype.cache = val
return val
Example #3
| Source File: _internal.py From Mastering-Elasticsearch-7.0 with MIT License | 6 votes |
|
def _getintp_ctype():
val = _getintp_ctype.cache
if val is not None:
return val
if ctypes is None:
import numpy as np
val = dummy_ctype(np.intp)
else:
char = dtype('p').char
if (char == 'i'):
val = ctypes.c_int
elif char == 'l':
val = ctypes.c_long
elif char == 'q':
val = ctypes.c_longlong
else:
val = ctypes.c_long
_getintp_ctype.cache = val
return val
Example #4
| Source File: _internal.py From Computable with MIT License | 6 votes |
|
def _getintp_ctype():
from .multiarray import dtype
val = _getintp_ctype.cache
if val is not None:
return val
char = dtype('p').char
import ctypes
if (char == 'i'):
val = ctypes.c_int
elif char == 'l':
val = ctypes.c_long
elif char == 'q':
val = ctypes.c_longlong
else:
val = ctypes.c_long
_getintp_ctype.cache = val
return val
Example #5
| Source File: _internal.py From GraphicDesignPatternByPython with MIT License | 6 votes |
|
def _getintp_ctype():
val = _getintp_ctype.cache
if val is not None:
return val
if ctypes is None:
import numpy as np
val = dummy_ctype(np.intp)
else:
char = dtype('p').char
if (char == 'i'):
val = ctypes.c_int
elif char == 'l':
val = ctypes.c_long
elif char == 'q':
val = ctypes.c_longlong
else:
val = ctypes.c_long
_getintp_ctype.cache = val
return val
Example #6
| Source File: _internal.py From vnpy_crypto with MIT License | 6 votes |
|
def _getintp_ctype():
val = _getintp_ctype.cache
if val is not None:
return val
if ctypes is None:
import numpy as np
val = dummy_ctype(np.intp)
else:
char = dtype('p').char
if (char == 'i'):
val = ctypes.c_int
elif char == 'l':
val = ctypes.c_long
elif char == 'q':
val = ctypes.c_longlong
else:
val = ctypes.c_long
_getintp_ctype.cache = val
return val
Example #7
| Source File: __init__.py From afnumpy with BSD 2-Clause "Simplified" License | 6 votes |
|
def inplace_setitem(self, key, val):
try:
n_dims = self.numdims()
if (arrayfire.util._is_number(val)):
tdims = arrayfire.array._get_assign_dims(key, self.dims())
other_arr = arrayfire.array.constant_array(val, tdims[0], tdims[1], tdims[2], tdims[3], self.type())
del_other = True
else:
other_arr = val.arr
del_other = False
inds = arrayfire.array._get_indices(key)
# In place assignment. Notice passing a pointer to self.arr as output
arrayfire.util.safe_call(arrayfire.backend.get().af_assign_gen(ctypes.pointer(self.arr),
self.arr, ctypes.c_longlong(n_dims),
inds.pointer,
other_arr))
if del_other:
arrayfire.safe_call(arrayfire.backend.get().af_release_array(other_arr))
except RuntimeError as e:
raise IndexError(str(e))
Example #8
| Source File: _internal.py From lambda-packs with MIT License | 6 votes |
|
def _getintp_ctype():
val = _getintp_ctype.cache
if val is not None:
return val
if ctypes is None:
import numpy as np
val = dummy_ctype(np.intp)
else:
char = dtype('p').char
if (char == 'i'):
val = ctypes.c_int
elif char == 'l':
val = ctypes.c_long
elif char == 'q':
val = ctypes.c_longlong
else:
val = ctypes.c_long
_getintp_ctype.cache = val
return val
Example #9
| Source File: _internal.py From Fluid-Designer with GNU General Public License v3.0 | 6 votes |
|
def _getintp_ctype():
from .multiarray import dtype
val = _getintp_ctype.cache
if val is not None:
return val
char = dtype('p').char
import ctypes
if (char == 'i'):
val = ctypes.c_int
elif char == 'l':
val = ctypes.c_long
elif char == 'q':
val = ctypes.c_longlong
else:
val = ctypes.c_long
_getintp_ctype.cache = val
return val
Example #10
| Source File: _internal.py From pySINDy with MIT License | 6 votes |
|
def _getintp_ctype():
val = _getintp_ctype.cache
if val is not None:
return val
if ctypes is None:
import numpy as np
val = dummy_ctype(np.intp)
else:
char = dtype('p').char
if (char == 'i'):
val = ctypes.c_int
elif char == 'l':
val = ctypes.c_long
elif char == 'q':
val = ctypes.c_longlong
else:
val = ctypes.c_long
_getintp_ctype.cache = val
return val
Example #11
| Source File: _internal.py From mxnet-lambda with Apache License 2.0 | 6 votes |
|
def _getintp_ctype():
val = _getintp_ctype.cache
if val is not None:
return val
if ctypes is None:
import numpy as np
val = dummy_ctype(np.intp)
else:
char = dtype('p').char
if (char == 'i'):
val = ctypes.c_int
elif char == 'l':
val = ctypes.c_long
elif char == 'q':
val = ctypes.c_longlong
else:
val = ctypes.c_long
_getintp_ctype.cache = val
return val
Example #12
| Source File: _internal.py From ImageFusion with MIT License | 6 votes |
|
def _getintp_ctype():
from .multiarray import dtype
val = _getintp_ctype.cache
if val is not None:
return val
char = dtype('p').char
import ctypes
if (char == 'i'):
val = ctypes.c_int
elif char == 'l':
val = ctypes.c_long
elif char == 'q':
val = ctypes.c_longlong
else:
val = ctypes.c_long
_getintp_ctype.cache = val
return val
Example #13
| Source File: _internal.py From Splunking-Crime with GNU Affero General Public License v3.0 | 6 votes |
|
def _getintp_ctype():
val = _getintp_ctype.cache
if val is not None:
return val
if ctypes is None:
import numpy as np
val = dummy_ctype(np.intp)
else:
char = dtype('p').char
if (char == 'i'):
val = ctypes.c_int
elif char == 'l':
val = ctypes.c_long
elif char == 'q':
val = ctypes.c_longlong
else:
val = ctypes.c_long
_getintp_ctype.cache = val
return val
Example #14
| Source File: archive_read.py From PyEasyArchive with GNU General Public License v2.0 | 6 votes |
|
def _read_by_block(archive_res):
buffer_ = ctypes.c_char_p()
num = ctypes.c_size_t()
offset = ctypes.c_longlong()
while 1:
r = libarchive.calls.archive_read.c_archive_read_data_block(
archive_res,
ctypes.cast(ctypes.byref(buffer_),
ctypes.POINTER(ctypes.c_void_p)),
ctypes.byref(num),
ctypes.byref(offset))
if r == libarchive.constants.archive.ARCHIVE_OK:
block = ctypes.string_at(buffer_, num.value)
assert len(block) == num.value
yield block
elif r == libarchive.constants.archive.ARCHIVE_EOF:
break
else:
raise ValueError("Read failed (archive_read_data_block): (%d)" %
(r,))
Example #15
| Source File: _internal.py From elasticintel with GNU General Public License v3.0 | 6 votes |
|
def _getintp_ctype():
val = _getintp_ctype.cache
if val is not None:
return val
if ctypes is None:
import numpy as np
val = dummy_ctype(np.intp)
else:
char = dtype('p').char
if (char == 'i'):
val = ctypes.c_int
elif char == 'l':
val = ctypes.c_long
elif char == 'q':
val = ctypes.c_longlong
else:
val = ctypes.c_long
_getintp_ctype.cache = val
return val
Example #16
| Source File: elbow_wrapper.py From pyclustering with GNU General Public License v3.0 | 6 votes |
|
def elbow(sample, kmin, kmax, initializer, random_state):
random_state = random_state or -1
pointer_data = package_builder(sample, c_double).create()
ccore = ccore_library.get()
if initializer == elbow_center_initializer.KMEANS_PLUS_PLUS:
ccore.elbow_method_ikpp.restype = POINTER(pyclustering_package)
package = ccore.elbow_method_ikpp(pointer_data, c_size_t(kmin), c_size_t(kmax), c_longlong(random_state))
elif initializer == elbow_center_initializer.RANDOM:
ccore.elbow_method_irnd.restype = POINTER(pyclustering_package)
package = ccore.elbow_method_irnd(pointer_data, c_size_t(kmin), c_size_t(kmax), c_longlong(random_state))
else:
raise ValueError("Not supported type of center initializer '" + str(initializer) + "'.")
results = package_extractor(package).extract()
ccore.free_pyclustering_package(package)
return (results[elbow_package_indexer.ELBOW_PACKAGE_INDEX_AMOUNT][0],
results[elbow_package_indexer.ELBOW_PACKAGE_INDEX_WCE])
Example #17
| Source File: WnfDump.py From wnfun with BSD 2-Clause "Simplified" License | 6 votes |
|
def DoWrite(StateName, Data):
StateName = ctypes.c_longlong(int(StateName, 16))
dataBuffer = ctypes.c_char_p(Data)
bufferSize = len(Data)
status = ZwUpdateWnfStateData(ctypes.byref(StateName), dataBuffer, bufferSize, 0, 0, 0, 0)
status = ctypes.c_ulong(status).value
if status == 0:
return True
else:
print('[Error] Could not write for this statename: 0x{:x}'.format(status))
return False
#########################################################################################
############### MAIN ###############
Example #18
| Source File: wnfcom.py From wnfun with BSD 2-Clause "Simplified" License | 6 votes |
|
def SetStateName(self, WnfName):
tmpName = 0
try:
tmpName = g_WellKnownWnfNames[WnfName.upper()]
except:
if len(WnfName)>2 and WnfName[1] == 'x':
WnfName = WnfName[2:]
try:
tmpName = int(WnfName, 16)
except:
tmpName = 0
self.pprint("[Error] Could not validate the provided name")
return False
self.StateName = ctypes.c_longlong(tmpName)
self.internalName.value = ctypes.c_ulonglong(tmpName ^ WNF_STATE_KEY)
return True
Example #19
| Source File: _internal.py From coffeegrindsize with MIT License | 6 votes |
|
def _getintp_ctype():
val = _getintp_ctype.cache
if val is not None:
return val
if ctypes is None:
import numpy as np
val = dummy_ctype(np.intp)
else:
char = dtype('p').char
if (char == 'i'):
val = ctypes.c_int
elif char == 'l':
val = ctypes.c_long
elif char == 'q':
val = ctypes.c_longlong
else:
val = ctypes.c_long
_getintp_ctype.cache = val
return val
Example #20
| Source File: nervanamkl.py From neon with Apache License 2.0 | 6 votes |
|
def fprop_relu(self, layer, x, slope):
if layer is None:
layer = layer_mkl.ReluLayerMKL()
if not hasattr(x, 'shape5D'):
return self.maximum(x, 0) + slope * self.minimum(0, x)
if slope != 0:
self.convert(x)
x.clean_mkl()
return self.maximum(x, 0) + slope * self.minimum(0, x)
if x.shape5D is not None:
C, D, H, W, N = x.shape5D
else:
C, N = x._tensor.shape
D, H, W = 1, 1, 1
x.shape5D = C, D, H, W, N
layer.shape5D = C, D, H, W, N
primitives = c_longlong(layer.dnnPrimitives.ctypes.data)
if x.primitive[3] == 0:
layer.inputMKL = False
self.mklEngine.Relu_f(x.get_prim(), primitives, layer.initOk_f, N, C, H, W)
layer.initOk_f = 1
return x
Example #21
| Source File: nervanamkl.py From neon with Apache License 2.0 | 6 votes |
|
def compound_bprop_bn(self, deltas, grad_gamma, grad_beta,
error, inputs, xsum, xvar, gamma,
eps, binary=False, layer=None):
if not layer or not isinstance(layer.in_shape, tuple):
super(NervanaMKL, self).compound_bprop_bn(deltas, grad_gamma,
grad_beta, error,
inputs, xsum, xvar,
gamma, eps, binary,
layer)
return
primitives = c_longlong(layer.dnnPrimitives.ctypes.data)
self.mklEngine.BatchNormBackp(inputs.get_prim(), error.get_prim(),
deltas.get_prim(), grad_gamma.get_prim(),
grad_beta.get_prim(), layer.in_shape[0],
primitives, layer.init_b)
layer.init_b = 1
deltas.shape5D = layer.shape5D
Example #22
| Source File: _internal.py From Carnets with BSD 3-Clause "New" or "Revised" License | 6 votes |
|
def _getintp_ctype():
val = _getintp_ctype.cache
if val is not None:
return val
if ctypes is None:
import numpy as np
val = dummy_ctype(np.intp)
else:
char = dtype('p').char
if (char == 'i'):
val = ctypes.c_int
elif char == 'l':
val = ctypes.c_long
elif char == 'q':
val = ctypes.c_longlong
else:
val = ctypes.c_long
_getintp_ctype.cache = val
return val
Example #23
| Source File: api.py From aws-builders-fair-projects with Apache License 2.0 | 6 votes |
|
def _set_input(self, name, data):
"""Set the input using the input name with data
Parameters
__________
name : str
The name of an input.
data : list of numbers
The data to be set.
"""
in_data = np.ascontiguousarray(data, dtype=np.float32)
shape = np.array(in_data.shape, dtype=np.int64)
_check_call(_LIB.SetDLRInput(byref(self.handle),
c_char_p(name.encode('utf-8')),
shape.ctypes.data_as(POINTER(c_longlong)),
in_data.ctypes.data_as(POINTER(c_float)),
c_int(in_data.ndim)))
if self.backend == 'treelite':
self._lazy_init_output_shape()
Example #24
| Source File: api.py From aws-builders-fair-projects with Apache License 2.0 | 6 votes |
|
def _get_output_size_dim(self, index):
"""Get the size and the dimenson of the index-th output.
Parameters
__________
index : int
The index of the output.
Returns
_______
size : int
The size of the index-th output.
dim : int
The dimension of the index-th output.
"""
idx = ctypes.c_int(index)
size = ctypes.c_longlong()
dim = ctypes.c_int()
_check_call(_LIB.GetDLROutputSizeDim(byref(self.handle), idx,
byref(size), byref(dim)))
return size.value, dim.value
Example #25
| Source File: api.py From aws-builders-fair-projects with Apache License 2.0 | 6 votes |
|
def _get_output_shape(self, index):
"""Get the shape for the index-th output.
Parameters
__________
index : int
The index of the output.
Returns
_______
shape : list
The shape of the index-th output.
"""
size, dim = self._get_output_size_dim(index)
if not self.output_size_dim:
self.output_size_dim = [(0, 0)] * self._get_num_outputs()
self.output_size_dim[index] = (size, dim)
shape = np.zeros(dim, dtype=np.int64)
_check_call(_LIB.GetDLROutputShape(byref(self.handle),
c_int(index),
shape.ctypes.data_as(ctypes.POINTER(ctypes.c_longlong))))
return shape
Example #26
| Source File: _internal.py From Serverless-Deep-Learning-with-TensorFlow-and-AWS-Lambda with MIT License | 6 votes |
|
def _getintp_ctype():
val = _getintp_ctype.cache
if val is not None:
return val
if ctypes is None:
import numpy as np
val = dummy_ctype(np.intp)
else:
char = dtype('p').char
if (char == 'i'):
val = ctypes.c_int
elif char == 'l':
val = ctypes.c_long
elif char == 'q':
val = ctypes.c_longlong
else:
val = ctypes.c_long
_getintp_ctype.cache = val
return val
Example #27
| Source File: _internal.py From recruit with Apache License 2.0 | 6 votes |
|
def _getintp_ctype():
val = _getintp_ctype.cache
if val is not None:
return val
if ctypes is None:
import numpy as np
val = dummy_ctype(np.intp)
else:
char = dtype('p').char
if (char == 'i'):
val = ctypes.c_int
elif char == 'l':
val = ctypes.c_long
elif char == 'q':
val = ctypes.c_longlong
else:
val = ctypes.c_long
_getintp_ctype.cache = val
return val
Example #28
| Source File: nervanamkl.py From neon with Apache License 2.0 | 5 votes |
|
def sum_tensor(self, sum, layer_num, tensors, output, shape5D):
C, D, H, W, N = shape5D
inp = c_longlong(tensors.ctypes.data)
size = c_longlong(np.prod(output.shape))
prim = c_longlong(sum.ctypes.data)
self.mklEngine.MklSumTensor(layer_num, inp, size, output.get_prim(), prim, N, C, H, W)
Example #29
| Source File: nervanamkl.py From neon with Apache License 2.0 | 5 votes |
|
def compound_fprop_bn(self, x, xsum, xvar, gmean, gvar, gamma, beta, y,
eps, rho, compute_batch_sum,
accumbeta=0.0, relu=False, binary=False,
inference=False, outputs=None, layer=None):
if layer is None or outputs is None or not isinstance(layer.in_shape, tuple):
super(NervanaMKL, self).compound_fprop_bn(x, xsum, xvar, gmean, gvar,
gamma, beta, y, eps, rho,
compute_batch_sum,
accumbeta, relu, binary,
inference, outputs, layer
)
return
primitives = c_longlong(layer.dnnPrimitives.ctypes.data)
if len(layer.in_shape) == 3:
C = layer.in_shape[0]
H = layer.in_shape[1]
W = layer.in_shape[2]
D = 1
elif len(layer.in_shape) == 2:
C = layer.in_shape[0]
H = layer.in_shape[1]
W = layer.in_shape[1]
D = 1
elif len(layer.in_shape) == 4:
C = layer.in_shape[0]
H = layer.in_shape[1]
W = layer.in_shape[2]
D = layer.in_shape[3]
N = int(x.shape[-1]) // H // W // D # this is/corresponds to the batch size
gmean = c_longlong(gmean._tensor.ctypes.data)
gvar = c_longlong(gvar._tensor.ctypes.data)
self.mklEngine.BatchNormFprop(x.get_prim(), outputs.get_prim(),
gamma.get_prim(), beta.get_prim(), gmean, gvar,
c_float(rho), N, C, H, W * D, c_double(eps),
primitives, layer.init_f, c_int(inference))
layer.init_f = 1
layer.shape5D = outputs.shape5D = C, D, H, W, N
Example #30
| Source File: _internal.py From coffeegrindsize with MIT License | 5 votes |
|
def strides_as(self, obj):
"""
Return the strides tuple as an array of some other
c-types type. For example: ``self.strides_as(ctypes.c_longlong)``.
"""
if self._zerod:
return None
return (obj*self._arr.ndim)(*self._arr.strides)
