Esempio n. 1
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def create_deferred(type_inferer, node, deferred_cls):
    "Create a deferred type for an AST node"
    variable = Variable(None)
    deferred_type = deferred_cls(variable, type_inferer, node)
    variable.type = deferred_type
    node.variable = variable
    return deferred_type
Esempio n. 2
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def create_deferred(type_inferer, node, deferred_cls):
    "Create a deferred type for an AST node"
    variable = Variable(None)
    deferred_type = deferred_cls(variable, type_inferer, node)
    variable.type = deferred_type
    node.variable = variable
    return deferred_type
Esempio n. 3
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    def visit_ClosureNode(self, node):
        """
        Compile the inner function.
        """
        # Compile closure, skip CFA and type inference
        node.func_env.qualified_name = self.get_qname(node)
        numba.pipeline.run_env(self.env,
                               node.func_env,
                               pipeline_name='compile')

        translator = node.func_env.translator
        # translator.link()
        node.lfunc = translator.lfunc
        node.lfunc_pointer = translator.lfunc_pointer

        if node.need_numba_func:
            return self.create_numba_function(node, node.func_env)
        else:
            func_name = node.func_def.name
            self.symtab[func_name] = Variable(name=func_name,
                                              type=node.type,
                                              is_local=True)
            # return nodes.LLVMValueRefNode(node.type, node.lfunc)
            # TODO: Remove assignment altogether!
            # return nodes.NoneNode()
            return nodes.ObjectInjectNode(None, type=object_)
Esempio n. 4
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    def visit_ClosureNode(self, node):
        """
        Compile the inner function.
        """
        # Compile inner function, skip type inference
        order = numba.pipeline.Pipeline.order
        order = order[order.index('type_infer') + 1:]
        p, result = numba.pipeline.run_pipeline(
            self.context,
            node.py_func,
            node.type_inferred_ast,
            node.type.signature,
            symtab=node.symtab,
            order=order,  # skip type inference
        )

        node.lfunc = p.translator.lfunc
        node.lfunc_pointer = p.translator.lfunc_pointer

        if node.need_numba_func:
            return self.create_numba_function(node, p)
        else:
            func_name = node.func_def.name
            self.symtab[func_name] = Variable(name=func_name,
                                              type=node.type,
                                              is_local=True)
            return ast.Pass()
Esempio n. 5
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def _int(typesystem, node, x, base, dst_type=int_):
    # Resolve int(x) and float(x) to an equivalent cast

    if len(node.args) < 2:
        return cast(node, dst_type)

    node.variable = Variable(dst_type)
    return node
Esempio n. 6
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def build_wrapper_translation(env, llvm_module=None):
    """
    Generate a wrapper function in the given llvm module.
    """
    from numba import pipeline

    if llvm_module:
        wrapper_module = llvm_module
    else:
        wrapper_module = env.llvm_context.module

    # Create wrapper code generator and wrapper AST
    func_name = '__numba_wrapper_%s' % env.crnt.func_name
    signature = object_(void.pointer(), object_)
    symtab = dict(self=Variable(object_, is_local=True),
                  args=Variable(object_, is_local=True))

    func_env = env.crnt.inherit(
            func=fake_pyfunc,
            name=func_name,
            mangled_name=None, # Force FunctionEnvironment.init()
                               # to generate a new mangled name.
            func_signature=signature,
            locals={},
            symtab=symtab,
            refcount_args=False,
            llvm_module=wrapper_module)

    # Create wrapper LLVM function
    func_env.lfunc = pipeline.get_lfunc(env, func_env)

    # Build wrapper ast
    wrapper_node = build_wrapper_function_ast(env,
                                              wrapper_lfunc=func_env.lfunc,
                                              llvm_module=wrapper_module)
    func_env.ast = wrapper_node

    # Specialize and compile wrapper
    pipeline.run_env(env, func_env, pipeline_name='late_translate')
    keep_alive(fake_pyfunc, func_env.lfunc)

    return func_env.translator # TODO: Amend callers to eat func_env
Esempio n. 7
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    def visit_FunctionDef(self, node):
        if self.function_level == 0:
            return self._visit_func_children(node)

        signature = self._process_decorators(node)
        type = numba_types.ClosureType(signature)
        self.symtab[node.name] = Variable(type, is_local=True)

        closure = nodes.ClosureNode(node, type, self.func)
        type.closure = closure
        self.ast.closures.append(closure)

        return closure
Esempio n. 8
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def abs_(context, node, x):
    import builtinmodule

    argtype = get_type(x)

    if argtype.is_array and argtype.is_numeric:
        # Handle np.abs() on arrays
        dtype = builtinmodule.abstype(argtype.dtype)
        result_type = argtype.copy(dtype=dtype)
        node.variable = Variable(result_type)
        return node

    return builtinmodule.abs_(context, node, x)
Esempio n. 9
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def infer_unary_math_call(context, call_node, arg, default_result_type=double):
    "Resolve calls to math functions to llvm.log.f32() etc"
    # signature is a generic signature, build a correct one
    type = get_type(call_node.args[0])

    if type.is_numeric and type.kind < default_result_type.kind:
        type = default_result_type
    elif type.is_array and type.dtype.is_int:
        type = type.copy(dtype=double)

    # signature = minitypes.FunctionType(return_type=type, args=[type])
    # result = nodes.MathNode(py_func, signature, call_node.args[0])
    nodes.annotate(context.env, call_node, is_math=True)
    call_node.variable = Variable(type)
    return call_node
Esempio n. 10
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def abs_(typesystem, node, x):
    from . import builtinmodule

    argtype = get_type(x)
    nodes.annotate(typesystem.env, node, is_math=True)

    if argtype.is_array and argtype.dtype.is_numeric:
        # Handle np.abs() on arrays
        dtype = builtinmodule.abstype(argtype.dtype)
        result_type = argtype.add('dtype', dtype)
        node.variable = Variable(result_type)
    else:
        node = builtinmodule.abs_(typesystem, node, x)

    return node
Esempio n. 11
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def round_(typesystem, node, number, ndigits):
    argtype = get_type(number)

    if len(node.args) == 1 and argtype.is_int:
        # round(myint) -> float(myint)
        return nodes.CoercionNode(node.args[0], double)

    if argtype.is_float or argtype.is_int:
        dst_type = double
    else:
        dst_type = object_
        node.args[0] = nodes.CoercionNode(node.args[0], object_)

    node.variable = Variable(dst_type)
    return node # nodes.CoercionNode(node, double)
Esempio n. 12
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def round_(context, node, number, ndigits):
    # is_math = is_math_function(node.args, round)
    argtype = get_type(number)

    if len(node.args) == 1 and argtype.is_int:
        # round(myint) -> float(myint)
        return nodes.CoercionNode(node.args[0], double)

    if argtype.is_float or argtype.is_int:
        dst_type = double
    else:
        dst_type = object_
        node.args[0] = nodes.CoercionNode(node.args[0], object_)

    node.variable = Variable(dst_type)
    return node  # nodes.CoercionNode(node, double)
Esempio n. 13
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    def infer(typesystem, call_node, *args):
        "Resolve calls to llvmmath math calls"
        # signature is a generic signature, build a correct one
        type = reduce(typesystem.promote, map(get_type, call_node.args))

        if type.is_numeric and rank(type) < rank(default_result_type):
            type = default_result_type
        elif type.is_array and type.dtype.is_int:
            type = typesystem.array(double, type.ndim)

        call_node.args[:] = nodes.CoercionNode.coerce(call_node.args, type)

        # TODO: Remove the abuse below
        nodes.annotate(typesystem.env, call_node, is_math=True)
        call_node.variable = Variable(type)
        return call_node
Esempio n. 14
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    def update_closures(self, func_def, scope_type, ext_type):
        # Patch closures to get the closure scope as the first argument
        for closure in func_def.closures:
            # closure.scope_type = scope_type
            closure.func_def.scope_type = scope_type
            closure.ext_type = ext_type

            # patch function parameters
            param = ast.Name(id=CLOSURE_SCOPE_ARG_NAME, ctx=ast.Param())
            param.variable = Variable(scope_type, is_local=True)
            param.type = param.variable.type

            closure.symtab[CLOSURE_SCOPE_ARG_NAME] = param.variable
            closure.func_def.args.args.insert(0, param)
            closure.need_closure_scope = True

            # patch closure signature
            closure.type.signature.args = (
                scope_type, ) + closure.type.signature.args
Esempio n. 15
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 def _load_name(self, var_name, is_cellvar=False):
     src = ast.Name(var_name, ast.Load())
     src.variable = Variable.from_variable(self.symtab[var_name])
     src.variable.is_cellvar = is_cellvar
     src.type = src.variable.type
     return src
Esempio n. 16
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def pow_(context, call_node, node, power, mod=None):
    dst_type = binop_type(context, node, power)
    call_node.variable = Variable(dst_type)
    return call_node
Esempio n. 17
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 def _load_name(self, var_name, is_cellvar=False):
     src = ast.Name(var_name, ast.Load())
     src.variable = Variable.from_variable(self.symtab[var_name])
     src.variable.is_cellvar = is_cellvar
     src.type = src.variable.type
     return src
Esempio n. 18
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def typednode(node, type):
    "Set a type and simple typed variable on a node"
    node.variable = Variable(type)
    node.type = type
    return node
Esempio n. 19
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 def get_vars_symtab(self):
     return dict(
         (var.temp_name,
          Variable(name=var.temp_name, is_local=True, type=var.type))
         for var in self.variables if not var.code)
Esempio n. 20
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def abs_(context, node, x):
    node.variable = Variable(abstype(get_type(x)))
    return node
Esempio n. 21
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def unellipsify(node, slices, subscript_node):
    """
    Given an array node `node`, process all AST slices and create the
    final type:

        - process newaxes (None or numpy.newaxis)
        - replace Ellipsis with a bunch of ast.Slice objects
        - process integer indices
        - append any missing slices in trailing dimensions
    """
    type = node.variable.type

    if not type.is_array:
        assert type.is_object
        return object_, node

    if (len(slices) == 1 and nodes.is_constant_index(slices[0]) and
            slices[0].value.pyval is Ellipsis):
        # A[...]
        return type, node

    result = []
    seen_ellipsis = False

    # Filter out newaxes
    newaxes = [newaxis for newaxis in slices if nodes.is_newaxis(newaxis)]
    n_indices = len(slices) - len(newaxes)

    full_slice = ast.Slice(lower=None, upper=None, step=None)
    full_slice.variable = Variable(typesystem.slice_)
    ast.copy_location(full_slice, slices[0])

    # process ellipses and count integer indices
    indices_seen = 0
    for slice_node in slices[::-1]:
        slice_type = slice_node.variable.type
        if slice_type.is_ellipsis:
            if seen_ellipsis:
                result.append(full_slice)
            else:
                nslices = type.ndim - n_indices + 1
                result.extend([full_slice] * nslices)
                seen_ellipsis = True
        elif (slice_type.is_slice or slice_type.is_int or
              nodes.is_newaxis(slice_node)):
            indices_seen += slice_type.is_int
            result.append(slice_node)
        else:
            # TODO: Coerce all object operands to integer indices?
            # TODO: (This will break indexing with the Ellipsis object or
            # TODO:  with slice objects that we couldn't infer)
            return object_, nodes.CoercionNode(node, object_)

    # Reverse our reversed processed list of slices
    result.reverse()

    # append any missing slices (e.g. a2d[:]
    result_length = len(result) - len(newaxes)
    if result_length < type.ndim:
        nslices = type.ndim - result_length
        result.extend([full_slice] * nslices)

    subscript_node.slice = ast.ExtSlice(result)
    ast.copy_location(subscript_node.slice, slices[0])

    # create the final array type and set it in value.variable
    result_dtype = node.variable.type.dtype
    result_ndim = node.variable.type.ndim + len(newaxes) - indices_seen
    if result_ndim > 0:
        result_type = result_dtype[(slice(None),) * result_ndim]
    elif result_ndim == 0:
        result_type = result_dtype
    else:
        result_type = object_

    return result_type, node
Esempio n. 22
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def abs_(typesystem, node, x):
    argtype = typesystem.promote(long_, get_type(x))
    dst_type = abstype(argtype)
    node.variable = Variable(dst_type)
    node.args = [nodes.CoercionNode(x, argtype)]
    return node
Esempio n. 23
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def range_(typesystem, node, start, stop, step):
    node.variable = Variable(typesystem.range_)
    node.args = nodes.CoercionNode.coerce(node.args, dst_type=Py_ssize_t)
    return node
Esempio n. 24
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def abs_(typesystem, node, x):
    node.variable = Variable(abstype(get_type(x)))
    return node