Spaces:
Running
on
Zero
Running
on
Zero
File size: 3,345 Bytes
9d3cb0a |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 |
import tempfile
import typing
import zipfile
from pathlib import Path
import markdown2 as md
import matplotlib.pyplot as plt
import torch
from IPython.display import HTML
def audio_table(
audio_dict: dict,
first_column: str = None,
format_fn: typing.Callable = None,
**kwargs,
): # pragma: no cover
"""Embeds an audio table into HTML, or as the output cell
in a notebook.
Parameters
----------
audio_dict : dict
Dictionary of data to embed.
first_column : str, optional
The label for the first column of the table, by default None
format_fn : typing.Callable, optional
How to format the data, by default None
Returns
-------
str
Table as a string
Examples
--------
>>> audio_dict = {}
>>> for i in range(signal_batch.batch_size):
>>> audio_dict[i] = {
>>> "input": signal_batch[i],
>>> "output": output_batch[i]
>>> }
>>> audiotools.post.audio_zip(audio_dict)
"""
from audiotools import AudioSignal
output = []
columns = None
def _default_format_fn(label, x, **kwargs):
if torch.is_tensor(x):
x = x.tolist()
if x is None:
return "."
elif isinstance(x, AudioSignal):
return x.embed(display=False, return_html=True, **kwargs)
else:
return str(x)
if format_fn is None:
format_fn = _default_format_fn
if first_column is None:
first_column = "."
for k, v in audio_dict.items():
if not isinstance(v, dict):
v = {"Audio": v}
v_keys = list(v.keys())
if columns is None:
columns = [first_column] + v_keys
output.append(" | ".join(columns))
layout = "|---" + len(v_keys) * "|:-:"
output.append(layout)
formatted_audio = []
for col in columns[1:]:
formatted_audio.append(format_fn(col, v[col], **kwargs))
row = f"| {k} | "
row += " | ".join(formatted_audio)
output.append(row)
output = "\n" + "\n".join(output)
return output
def in_notebook(): # pragma: no cover
"""Determines if code is running in a notebook.
Returns
-------
bool
Whether or not this is running in a notebook.
"""
try:
from IPython import get_ipython
if "IPKernelApp" not in get_ipython().config: # pragma: no cover
return False
except ImportError:
return False
except AttributeError:
return False
return True
def disp(obj, **kwargs): # pragma: no cover
"""Displays an object, depending on if its in a notebook
or not.
Parameters
----------
obj : typing.Any
Any object to display.
"""
from audiotools import AudioSignal
IN_NOTEBOOK = in_notebook()
if isinstance(obj, AudioSignal):
audio_elem = obj.embed(display=False, return_html=True)
if IN_NOTEBOOK:
return HTML(audio_elem)
else:
print(audio_elem)
if isinstance(obj, dict):
table = audio_table(obj, **kwargs)
if IN_NOTEBOOK:
return HTML(md.markdown(table, extras=["tables"]))
else:
print(table)
if isinstance(obj, plt.Figure):
plt.show()
|