Model summary: add 1 decimal place (#4745)

Show 1999 parameters as 1.9 K and 1000 parameters as 1.0 K, rather than both as 1 K.

Co-authored-by: chaton <thomas@grid.ai>
Co-authored-by: Jirka Borovec <Borda@users.noreply.github.com>
Co-authored-by: Sean Naren <sean.narenthiran@gmail.com>
(cherry picked from commit 8dfbf63)

docs/source/debugging.rst

@@ -102,7 +102,7 @@ You can also display the intermediate input- and output sizes of all your layers
  --------------------------------------------------------------
  0 | net | Sequential | 132 K | [10, 256] | [10, 512]
  1 | net.0 | Linear | 131 K | [10, 256] | [10, 512]
- 2 | net.1 | BatchNorm1d | 1 K | [10, 512] | [10, 512]
+ 2 | net.1 | BatchNorm1d | 1.0 K | [10, 512] | [10, 512]
 
 when you call ``.fit()`` on the Trainer. This can help you find bugs in the composition of your layers.
 

pytorch_lightning/core/memory.py

@@ -160,7 +160,7 @@ class ModelSummary(object):
  --------------------------------------------------------------
  0 | net | Sequential | 132 K | [10, 256] | [10, 512]
  1 | net.0 | Linear | 131 K | [10, 256] | [10, 512]
- 2 | net.1 | BatchNorm1d | 1 K | [10, 512] | [10, 512]
+ 2 | net.1 | BatchNorm1d | 1.0 K | [10, 512] | [10, 512]
  """
 
  MODE_TOP = "top"
@@ -363,13 +363,13 @@ def get_human_readable_count(number: int) -> str:
  >>> get_human_readable_count(123)
  '123 '
  >>> get_human_readable_count(1234) # (one thousand)
- '1 K'
+ '1.2 K'
  >>> get_human_readable_count(2e6) # (two million)
- '2 M'
+ '2.0 M'
  >>> get_human_readable_count(3e9) # (three billion)
- '3 B'
- >>> get_human_readable_count(4e12) # (four trillion)
- '4 T'
+ '3.0 B'
+ >>> get_human_readable_count(4e14) # (four hundred trillion)
+ '400 T'
  >>> get_human_readable_count(5e15) # (more than trillion)
  '5,000 T'
 
@@ -388,4 +388,7 @@ def get_human_readable_count(number: int) -> str:
  shift = -3 * (num_groups - 1)
  number = number * (10 ** shift)
  index = num_groups - 1
- return f"{int(number):,d} {labels[index]}"
+ if index < 1 or number >= 100:
+ return f"{int(number):,d} {labels[index]}"
+ else:
+ return f"{number:,.1f} {labels[index]}"