Source code for gpflow.experimental.check_shapes.specs

# Copyright 2022 The GPflow Contributors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
"""
Code for specifying expectations around shapes.
"""
from dataclasses import dataclass
from typing import Optional, Tuple

from .argument_ref import ArgumentRef
from .bool_specs import ParsedBoolSpec


@dataclass(frozen=True)
class ParsedNoteSpec:
    note: str

    def __repr__(self) -> str:
        return f"# {self.note}"


@dataclass(frozen=True)
class ParsedDimensionSpec:
    constant: Optional[int]
    variable_name: Optional[str]
    variable_rank: bool
    broadcastable: bool

    def __post_init__(self) -> None:
        assert (
            self.variable_name is None or self.constant is None
        ), "Dimension cannot be both constant and variable."
        if self.variable_rank:
            assert self.constant is None, "Constants cannot have a variable rank."

    def __repr__(self) -> str:
        tokens = []

        if self.broadcastable:
            tokens.append("broadcast ")

        if self.constant is not None:
            tokens.append(str(self.constant))
        elif self.variable_name:
            tokens.append(self.variable_name)
        else:
            if not self.variable_rank:
                tokens.append(".")

        if self.variable_rank:
            tokens.append("...")

        return "".join(tokens)


@dataclass(frozen=True)
class ParsedShapeSpec:
    dims: Tuple[ParsedDimensionSpec, ...]

    def __repr__(self) -> str:
        dims = [repr(dim) for dim in self.dims]
        return f"[{', '.join(dims)}]"


@dataclass(frozen=True)
class ParsedTensorSpec:
    shape: ParsedShapeSpec
    note: Optional[ParsedNoteSpec]

    def __repr__(self) -> str:
        note_str = f"  {self.note}" if self.note is not None else ""
        return f"{self.shape}{note_str}"


@dataclass(frozen=True)
class ParsedArgumentSpec:
    argument_ref: ArgumentRef
    tensor: ParsedTensorSpec
    condition: Optional[ParsedBoolSpec]

    def __repr__(self) -> str:
        tokens = []
        tokens.append(f"{self.argument_ref}: ")
        tokens.append(repr(self.tensor.shape))

        if self.condition is not None:
            tokens.append(" if ")
            tokens.append(repr(self.condition))

        if self.tensor.note is not None:
            tokens.append("  ")
            tokens.append(repr(self.tensor.note))

        return "".join(tokens)


@dataclass(frozen=True)
class ParsedFunctionSpec:
    arguments: Tuple[ParsedArgumentSpec, ...]
    notes: Tuple[ParsedNoteSpec, ...]

    def __repr__(self) -> str:
        lines = [repr(argument) for argument in self.arguments] + [
            repr(note) for note in self.notes
        ]
        return "\n".join(lines)