#!/usr/bin/env python3

# Copyright 2016 The TensorFlow Authors. 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
#
#     https://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.
# ==============================================================================

"""
This is mostly a copy of:
https://github.com/tensorflow/tensorflow/blob/master/tensorflow/python/tools/inspect_checkpoint.py

A simple script for inspect checkpoint files.

We extended it a bit.
"""

from __future__ import annotations

import _setup_returnn_env  # noqa
from typing import Dict, Any
import sys
import argparse
import numpy

from tensorflow.python.platform import app
from tensorflow.python.platform import flags
import returnn.tf.compat as tf_compat

FLAGS = None


def print_tensor(v):
    """
    :param numpy.ndarray v:
    """
    print(v)
    # See :func:`variable_scalar_summaries_dict`.
    mean = numpy.mean(v)
    print("mean:", mean)
    print("stddev:", numpy.sqrt(numpy.mean(numpy.square(v - mean))))
    print("rms:", numpy.sqrt(numpy.mean(numpy.square(v))))
    print("min:", numpy.min(v))
    print("max:", numpy.max(v))


def print_tensors_in_checkpoint_file(file_name, tensor_name, all_tensors):
    """Prints tensors in a checkpoint file.

    If no `tensor_name` is provided, prints the tensor names and shapes
    in the checkpoint file.

    If `tensor_name` is provided, prints the content of the tensor.

    Args:
      file_name: Name of the checkpoint file.
      tensor_name: Name of the tensor in the checkpoint file to print.
      all_tensors: Boolean indicating whether to print all tensors.
    """
    try:
        reader = tf_compat.v1.train.NewCheckpointReader(file_name)
        if all_tensors:
            var_to_shape_map = reader.get_variable_to_shape_map()
            for key in sorted(var_to_shape_map):
                print("tensor_name: ", key)
                print(reader.get_tensor(key))
        elif not tensor_name:
            print(reader.debug_string().decode("utf-8"))
        else:
            print("tensor_name: ", tensor_name)
            v = reader.get_tensor(tensor_name)
            print_tensor(v)
            if tensor_name.endswith("/Adam") and reader.has_tensor(tensor_name + "_1"):
                # https://github.com/tensorflow/tensorflow/blob/03beb65cecbc1e49ea477bca7f54543134b31d53/tensorflow/core/kernels/training_ops_gpu.cu.cc
                print("Guessing Adam m/v")
                v2 = reader.get_tensor(tensor_name + "_1")
                eps = 1e-8
                print("Adam update (m / (eps + sqrt(v))) with eps=%r:" % eps)
                print_tensor(v / (eps + numpy.sqrt(v2)))
    except Exception as e:  # pylint: disable=broad-except
        print(str(e))
        if "corrupted compressed block contents" in str(e):
            print("It's likely that your checkpoint file has been compressed with SNAPPY.")
        if "Data loss" in str(e) and (any([e in file_name for e in [".index", ".meta", ".data"]])):
            proposed_file = ".".join(file_name.split(".")[0:-1])
            v2_file_error_template = """
It's likely that this is a V2 checkpoint and you need to provide the filename
*prefix*.  Try removing the '.' and extension.  Try:
inspect checkpoint --file_name = {}"""
            print(v2_file_error_template.format(proposed_file))


def parse_numpy_printoption(kv_str):
    """Sets a single numpy printoption from a string of the form 'x=y'.

    See documentation on numpy.set_printoptions() for details about what values
    x and y can take. x can be any option listed there other than 'formatter'.

    Args:
      kv_str: A string of the form 'x=y', such as 'threshold=100000'

    Raises:
      argparse.ArgumentTypeError: If the string couldn't be used to set any
          nump printoption.
    """
    k_v_str = kv_str.split("=", 1)
    if len(k_v_str) != 2 or not k_v_str[0]:
        raise argparse.ArgumentTypeError("'%s' is not in the form k=v." % kv_str)
    k, v_str = k_v_str
    printoptions: Dict[str, Any] = numpy.get_printoptions()
    if k not in printoptions:
        raise argparse.ArgumentTypeError("'%s' is not a valid printoption." % k)
    v_type = type(printoptions[k])
    if printoptions[k] is None:
        raise argparse.ArgumentTypeError("Setting '%s' from the command line is not supported." % k)
    try:
        v = v_type(v_str) if v_type is not bool else flags.BooleanParser().parse(v_str)
    except ValueError as e:
        raise argparse.ArgumentTypeError(str(e))
    numpy.set_printoptions(**{k: v})


# noinspection PyUnusedLocal
def main(unused_argv):
    """
    Main entry:
    """
    if not FLAGS.file_name:
        print("Usage: inspect_checkpoint --file_name=checkpoint_file_name [--tensor_name=tensor_to_print]")
        sys.exit(1)
    else:
        print_tensors_in_checkpoint_file(FLAGS.file_name, FLAGS.tensor_name, FLAGS.all_tensors)


if __name__ == "__main__":
    parser = argparse.ArgumentParser()
    parser.register("type", "bool", lambda v: v.lower() == "true")
    parser.add_argument(
        "--file_name",
        type=str,
        default="",
        help="Checkpoint filename. "
        "Note, if using Checkpoint V2 format, file_name is the "
        "shared prefix between all files in the checkpoint.",
    )
    parser.add_argument("--tensor_name", type=str, default="", help="Name of the tensor to inspect")
    parser.add_argument(
        "--all_tensors",
        nargs="?",
        const=True,
        type=bool,
        default=False,
        help="If True, print the values of all the tensors.",
    )
    parser.add_argument(
        "--printoptions",
        nargs="*",
        type=parse_numpy_printoption,
        help="Argument for numpy.set_printoptions(), in the form 'k=v'.",
    )
    FLAGS, unparsed = parser.parse_known_args()
    app.run(main=main, argv=[sys.argv[0]] + unparsed)
