def write(self, values: base.LoggingData): with self.summary.as_default(): for key, value in values.items(): tf.summary.scalar(f'{self.label}/{_format_key(key)}', value, step=self._iter) self._iter += 1
def write(self, data: base.LoggingData): for k, v in data.items(): image = Image.fromarray(v, mode=self._mode) path = self._path / f'{k}_{self._indices[k]:06}.png' self._indices[k] += 1 with path.open(mode='wb') as f: logging.info('Writing image to %s.', str(path)) image.save(f)
def write(self, data: base.LoggingData, step: Optional[int] = None): """Writes a set of scalar values in the log at a specific time step Args: data: a dictionary with name of quantity: quantity pairs step: optionally the number of the step to register the data, if None, the internal is used """ if step is not None: iteration = step else: iteration = self._iter self._iter += 1 for key, value in data.items(): self._writer.add_scalar(key, value, iteration)
def write(self, values: base.LoggingData) -> None: # If this is in init, launchpad fails, # Error: tensorflow.python.framework.errors_impl.InvalidArgumentError: # Cannot convert a Tensor of dtype resource to a NumPy array. # Line: CloudPickler(file, protocol=protocol, buffer_callback # =buffer_callback).dump(obj) if self._summary is None: self._summary = tf.summary.create_file_writer(self._logdir) with self._summary.as_default(): for key, value in values.items(): if hasattr(value, "shape") and len(value.shape) > 0: self.histogram_summary(key, value) elif hasattr(value, "shape") or not isinstance(value, dict): self.scalar_summary(key, value) else: self.dict_summary(key, value) self._iter += 1
def serialize(values: base.LoggingData) -> str: """Converts `values` to a pretty-printed string. This takes a dictionary `values` whose keys are strings and returns a formatted string such that each [key, value] pair is separated by ' = ' and each entry is separated by ' | '. The keys are sorted alphabetically to ensure a consistent order, and snake case is split into words. For example: values = {'a': 1, 'b' = 2.33333333, 'c': 'hello', 'big_value': 10} # Returns 'A = 1 | B = 2.333 | Big Value = 10 | C = hello' values_string = serialize(values) Args: values: A dictionary with string keys. Returns: A formatted string. """ return ' | '.join(f'{_format_key(k)} = {_format_value(v)}' for k, v in sorted(values.items()))
def write(self, values: base.LoggingData): values = {k: v for k, v in values.items() if v is not None} self._to.write(values)
def write(self, data: base.LoggingData): if self._keep: data = {k: data[k] for k in self._keep} if self._drop: data = {k: v for k, v in data.items() if k not in self._drop} self._to.write(data)
def write(self, values: base.LoggingData): self._wandb.log({self.label + k: v for k, v in values.items()}) self._iter += 1