Exemple #1
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 def evaluate(self, interpreter_state, args):
     func_term = args[0]
     func_type = FuncType(VecType(1), VecType(1))
     arg_term = args[1].get()
     result = np.zeros(self.n)
     for i in range(self.n):
         arg_val = VectorTerm(np.array([arg_term[i]]))
         result_term = interpreter_state.blind_apply(
             func_term, func_type, arg_val, VecType(1))
         result[i] = result_term.get()[0]
     return VectorTerm(result)
Exemple #2
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    def evaluate(self, interpreter_state, args):
        func_val = args[0]
        accum_val = args[1]
        list_args = args[2].get()

        unary_func_type = FuncType(VecType(1), VecType(1))
        binary_func_type = FuncType(VecType(1), unary_func_type)
        for i in range(self.n):
            arg_val = VectorTerm(np.array([list_args[i]]))
            curry_man = interpreter_state.blind_apply(func_val,
                                                      binary_func_type,
                                                      arg_val, VecType(1))
            accum_val = interpreter_state.blind_apply(curry_man,
                                                      unary_func_type,
                                                      accum_val, VecType(1))
        return accum_val
Exemple #3
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    def evaluate(self, interpreter_state, args):
        first_func = args[1]
        first_func_type = FuncType(VecType(self.n), VecType(self.m))
        second_func = args[0]
        second_func_type = FuncType(VecType(self.m), VecType(self.p))
        arg_value = args[2]
        arg_type = VecType(self.n)

        middle_value = interpreter_state.blind_apply(first_func,
                                                     first_func_type,
                                                     arg_value, arg_type)
        middle_type = VecType(self.m)
        return interpreter_state.blind_apply(second_func, second_func_type,
                                             middle_value, middle_type)
Exemple #4
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 def required_arg_types(self):
     return [
         FuncType(VecType(self.m), VecType(self.p)),
         FuncType(VecType(self.n), VecType(self.m)),
         VecType(self.n)
     ]
Exemple #5
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 def ret_type(self):
     return VecType(self.n)
Exemple #6
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 def required_arg_types(self):
     return [VecType(self.n), VecType(self.m)]
Exemple #7
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 def required_arg_types(self):
     return [FuncType(VecType(1), VecType(1)), VecType(self.n)]
Exemple #8
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 def required_arg_types(self):
     return [VecType(1)]
Exemple #9
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def get_compose_type(n, m, p):
    return FuncType(
        FuncType(VecType(m), VecType(p)),
        FuncType(FuncType(VecType(n), VecType(m)),
                 FuncType(VecType(n), VecType(p))))
Exemple #10
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        term_app = TermApplication(func_ptr, arg_ptr)
        result_ptr = func_table.evaluate(self, term_app)
        return result_ptr

    def blind_apply(self, func_val, func_type, arg_val, arg_type):
        func_space = self.get_type_space(func_type)
        arg_space = self.get_type_space(arg_type)
        func_ptr = func_space.get_pointer(func_val)
        arg_ptr = arg_space.get_pointer(arg_val)
        result_ptr = self.apply_ptrs(func_ptr, arg_ptr)
        return result_ptr.get_term()


DIM = 10

scalar_t = VecType(1)
vector_t = VecType(DIM)
unary_vec_func_t = FuncType(vector_t, vector_t)
binary_vec_func_t = FuncType(vector_t, unary_vec_func_t)
unary_scalar_func_t = FuncType(scalar_t, scalar_t)
binary_scalar_func_t = FuncType(scalar_t, unary_scalar_func_t)
map_func_t = FuncType(unary_scalar_func_t, unary_vec_func_t)
vector_to_scalar_func_t = FuncType(vector_t, scalar_t)
reduce_func_t = FuncType(binary_scalar_func_t,
                         FuncType(scalar_t, vector_to_scalar_func_t))
fill_func_t = FuncType(scalar_t, vector_t)

interpreter_state = InterpreterState()

interpreter_state.add_type(map_func_t)
interpreter_state.add_type(fill_func_t)