import logging
import six
import plaidml2.edsl as edsl
from plaidml2.ffi import ffi, ffi_call, lib
logger = logging.getLogger(__name__)
def __init():
ffi_call(lib.plaidml_op_init)
ffi.init_once(__init, 'plaidml_op_init')
def op(op_name, args):
value = edsl.Value(args)
return edsl.Value(
ffi_call(lib.plaidml_op_make, op_name.encode(), value.as_ptr()))
def abs(x):
return op('abs', [x]).as_tensor()
def all(x, axis=None, keepdims=False):
return op('all', [x, axis, keepdims]).as_tensor()
from collections import namedtuple
import logging
import six
from plaidml2 import DType
from plaidml2.ffi import ForeignObject, ffi, ffi_call, lib
logger = logging.getLogger(__name__)
def __init():
ffi_call(lib.plaidml_edsl_init)
ffi.init_once(__init, 'plaidml_edsl_init')
class LogicalShape(ForeignObject):
__ffi_del__ = lib.plaidml_logical_shape_free
__ffi_repr__ = lib.plaidml_logical_shape_repr
def __init__(self, dtype=None, dims=[], ptr=None, layout=''):
if ptr:
ffi_obj = ptr
elif dtype is not None:
raw_dims = ffi.new('int64_t[]',
[0 if x is None else x for x in dims])
ffi_obj = ffi_call(lib.plaidml_logical_shape_alloc, dtype,
len(dims), raw_dims, layout.encode())
else:
# Copyright 2019 Intel Corporation.
import numpy as np
import plaidml2 as plaidml
import plaidml2.settings as plaidml_settings
from plaidml2.ffi import ForeignObject, decode_str, ffi, ffi_call, lib
def __init():
ffi_call(lib.plaidml_exec_init)
ffi.init_once(__init, 'plaidml_exec_init')
def list_devices():
ndevices = ffi_call(lib.plaidml_device_list_count)
raw_devices = ffi.new('plaidml_string*[]', ndevices)
ffi_call(lib.plaidml_device_list, ndevices, raw_devices)
return [decode_str(x) for x in raw_devices]
def list_targets():
ntargets = ffi_call(lib.plaidml_target_list_count)
raw_targets = ffi.new('plaidml_string*[]', ntargets)
ffi_call(lib.plaidml_target_list, ntargets, raw_targets)
return [decode_str(x) for x in raw_targets]
class Executable(ForeignObject):
import numpy as np
from plaidml2.core._version import PLAIDML_VERSION
from plaidml2.ffi import Error, ForeignObject, ffi, ffi_call, lib
def __init():
ffi_call(lib.plaidml_init)
lib_version = ffi.string(ffi_call(lib.plaidml_version)).decode()
if lib_version != PLAIDML_VERSION:
raise EnvironmentError(
'Version mismatch. plaidml (python): {}, {} (C++): {}'.format(
PLAIDML_VERSION, lib.lib_name, lib_version))
return PLAIDML_VERSION
__version__ = ffi.init_once(__init, 'plaidml_init')
@atexit.register
def __shutdown():
ffi_call(lib.plaidml_shutdown)
class DType(enum.IntEnum):
"""Describes the type of a tensor element."""
INVALID = 0
BOOLEAN = 2
INT8 = 0x10
INT16 = 0x11
INT32 = 0x12
INT64 = 0x13
