def log_text(self, log_name, x, y=None, timestamp=None):
"""Log text data in Neptune
| If a log with provided ``log_name`` does not exist, it is created automatically.
| If log exists (determined by ``log_name``), then new value is appended to it.
Args:
log_name (:obj:`str`): The name of log, i.e. `mse`, `my_text_data`, `timing_info`.
x (:obj:`double` or :obj:`str`): Depending, whether ``y`` parameter is passed:
* ``y`` not passed: The value of the log (data-point). Must be ``str``.
* ``y`` passed: Index of log entry being appended. Must be strictly increasing.
y (:obj:`str`, optional, default is ``None``): The value of the log (data-point).
timestamp (:obj:`time`, optional, default is ``None``):
Timestamp to be associated with log entry. Must be Unix time.
If ``None`` is passed, `time.time() <https://docs.python.org/3.6/library/time.html#time.time>`_
(Python 3.6 example) is invoked to obtain timestamp.
Example:
Assuming that `experiment` is an instance of :class:`~neptune.experiments.Experiment`:
.. code:: python3
# common case, where log name and data are passed
neptune.log_text('my_text_data', str(data_item))
# log_name, x and timestamp are passed
neptune.log_text(log_name='logging_losses_as_text',
x=str(val_loss),
timestamp=1560430912)
Note:
For efficiency, logs are uploaded in batches via a queue.
Hence, if you log a lot of data, you may experience slight delays in Neptune web application.
Note:
Passing ``x`` coordinate as NaN or +/-inf causes this log entry to be ignored.
Warning is printed to ``stdout``.
"""
x, y = self._get_valid_x_y(x, y)
if x is not None and is_nan_or_inf(x):
x = None
if not isinstance(y, six.string_types):
raise InvalidChannelValue(expected_type="str",
actual_type=type(y).__name__)
if x is not None and is_nan_or_inf(x):
_logger.warning(
"Invalid metric x-coordinate: %s for channel %s. "
"Metrics with nan or +/-inf x-coordinates will not be sent to server",
x,
log_name,
)
else:
value = ChannelValue(x, dict(text_value=y), timestamp)
self._channels_values_sender.send(log_name, ChannelType.TEXT.value,
value)
def log_image(self,
log_name,
x,
y=None,
image_name=None,
description=None,
timestamp=None):
"""Log image data in Neptune
| If a log with provided ``log_name`` does not exist, it is created automatically.
| If log exists (determined by ``log_name``), then new value is appended to it.
Args:
log_name (:obj:`str`): The name of log, i.e. `bboxes`, `visualisations`, `sample_images`.
x (:obj:`double`): Depending, whether ``y`` parameter is passed:
* ``y`` not passed: The value of the log (data-point). See ``y`` parameter.
* ``y`` passed: Index of log entry being appended. Must be strictly increasing.
y (multiple types supported, optional, default is ``None``):
The value of the log (data-point). Can be one of the following types:
* :obj:`PIL image`
`Pillow docs <https://pillow.readthedocs.io/en/latest/reference/Image.html#image-module>`_
* :obj:`matplotlib.figure.Figure`
`Matplotlib 3.1.1 docs <https://matplotlib.org/3.1.1/api/_as_gen/matplotlib.figure.Figure.html>`_
* :obj:`str` - path to image file
* 2-dimensional :obj:`numpy.array` - interpreted as grayscale image
* 3-dimensional :obj:`numpy.array` - behavior depends on last dimension
* if last dimension is 1 - interpreted as grayscale image
* if last dimension is 3 - interpreted as RGB image
* if last dimension is 4 - interpreted as RGBA image
image_name (:obj:`str`, optional, default is ``None``): Image name
description (:obj:`str`, optional, default is ``None``): Image description
timestamp (:obj:`time`, optional, default is ``None``):
Timestamp to be associated with log entry. Must be Unix time.
If ``None`` is passed, `time.time() <https://docs.python.org/3.6/library/time.html#time.time>`_
(Python 3.6 example) is invoked to obtain timestamp.
Example:
Assuming that `experiment` is an instance of :class:`~neptune.experiments.Experiment`:
.. code:: python3
# path to image file
experiment.log_image('bbox_images', 'pictures/image.png')
experiment.log_image('bbox_images', x=5, 'pictures/image.png')
experiment.log_image('bbox_images', 'pictures/image.png', image_name='difficult_case')
# PIL image
img = PIL.Image.new('RGB', (60, 30), color = 'red')
experiment.log_image('fig', img)
# 2d numpy array
array = numpy.random.rand(300, 200)*255
experiment.log_image('fig', array)
# 3d grayscale array
array = numpy.random.rand(300, 200, 1)*255
experiment.log_image('fig', array)
# 3d RGB array
array = numpy.random.rand(300, 200, 3)*255
experiment.log_image('fig', array)
# 3d RGBA array
array = numpy.random.rand(300, 200, 4)*255
experiment.log_image('fig', array)
# matplotlib figure example 1
from matplotlib import pyplot
pyplot.plot([1, 2, 3, 4])
pyplot.ylabel('some numbers')
experiment.log_image('plots', plt.gcf())
# matplotlib figure example 2
from matplotlib import pyplot
import numpy
numpy.random.seed(19680801)
data = numpy.random.randn(2, 100)
figure, axs = pyplot.subplots(2, 2, figsize=(5, 5))
axs[0, 0].hist(data[0])
axs[1, 0].scatter(data[0], data[1])
axs[0, 1].plot(data[0], data[1])
axs[1, 1].hist2d(data[0], data[1])
experiment.log_image('diagrams', figure)
Note:
For efficiency, logs are uploaded in batches via a queue.
Hence, if you log a lot of data, you may experience slight delays in Neptune web application.
Note:
Passing ``x`` coordinate as NaN or +/-inf causes this log entry to be ignored.
Warning is printed to ``stdout``.
Warning:
Only images up to 2MB are supported. Larger files will not be logged to Neptune.
"""
x, y = self._get_valid_x_y(x, y)
if x is not None and is_nan_or_inf(x):
x = None
image_content = get_image_content(y)
if len(image_content) > self.IMAGE_SIZE_LIMIT:
_logger.warning(
'Your image is larger than 2MB. Neptune supports logging images smaller than 2MB. '
'Resize or increase compression of this image')
image_content = None
input_image = dict(name=image_name, description=description)
if image_content:
input_image['data'] = base64.b64encode(image_content).decode(
'utf-8')
if x is not None and is_nan_or_inf(x):
_logger.warning(
'Invalid metric x-coordinate: %s for channel %s. '
'Metrics with nan or +/-inf x-coordinates will not be sent to server',
x, log_name)
else:
value = ChannelValue(x, dict(image_value=input_image), timestamp)
self._channels_values_sender.send(log_name,
ChannelType.IMAGE.value, value)
def log_metric(self, log_name, x, y=None, timestamp=None):
"""Log metrics (numeric values) in Neptune
| If a log with provided ``log_name`` does not exist, it is created automatically.
| If log exists (determined by ``log_name``), then new value is appended to it.
Args:
log_name (:obj:`str`): The name of log, i.e. `mse`, `loss`, `accuracy`.
x (:obj:`double`): Depending, whether ``y`` parameter is passed:
* ``y`` not passed: The value of the log (data-point).
* ``y`` passed: Index of log entry being appended. Must be strictly increasing.
y (:obj:`double`, optional, default is ``None``): The value of the log (data-point).
timestamp (:obj:`time`, optional, default is ``None``):
Timestamp to be associated with log entry. Must be Unix time.
If ``None`` is passed, `time.time() <https://docs.python.org/3.6/library/time.html#time.time>`_
(Python 3.6 example) is invoked to obtain timestamp.
Example:
Assuming that `experiment` is an instance of :class:`~neptune.experiments.Experiment` and
'accuracy' log does not exists:
.. code:: python3
# Both calls below have the same effect
# Common invocation, providing log name and value
experiment.log_metric('accuracy', 0.5)
experiment.log_metric('accuracy', 0.65)
experiment.log_metric('accuracy', 0.8)
# Providing both x and y params
experiment.log_metric('accuracy', 0, 0.5)
experiment.log_metric('accuracy', 1, 0.65)
experiment.log_metric('accuracy', 2, 0.8)
Note:
For efficiency, logs are uploaded in batches via a queue.
Hence, if you log a lot of data, you may experience slight delays in Neptune web application.
Note:
Passing either ``x`` or ``y`` coordinate as NaN or +/-inf causes this log entry to be ignored.
Warning is printed to ``stdout``.
"""
x, y = self._get_valid_x_y(x, y)
if not is_float(y):
raise InvalidChannelValue(expected_type='float',
actual_type=type(y).__name__)
if is_nan_or_inf(y):
_logger.warning(
'Invalid metric value: %s for channel %s. '
'Metrics with nan or +/-inf values will not be sent to server',
y, log_name)
elif x is not None and is_nan_or_inf(x):
_logger.warning(
'Invalid metric x-coordinate: %s for channel %s. '
'Metrics with nan or +/-inf x-coordinates will not be sent to server',
x, log_name)
else:
value = ChannelValue(x, dict(numeric_value=y), timestamp)
self._channels_values_sender.send(log_name,
ChannelType.NUMERIC.value, value)
