def __repr__(steps):
for name, tr in self._transformers:
model_fields.append(
(name, _precomputed_field(self._compact_class_repr(tr))))
return _toolkit_repr_print(steps, [model_fields],
width=8,
section_titles=["Steps"])
def __repr__(self):
"""
Print a string description of the model when the model name is entered
in the terminal.
"""
key_str = "{:<{}}: {}"
width = 30
(sections, section_titles) = self._get_summary_struct()
out = _toolkit_repr_print(self, sections, section_titles, width=width)
extra = []
extra.append(key_str.format("Accessible fields", width, ""))
extra.append(
key_str.format("m.topics", width,
"An SFrame containing the topics."))
extra.append(
key_str.format(
"m.vocabulary", width,
"An SArray containing the words in the vocabulary."))
extra.append(key_str.format("Useful methods", width, ""))
extra.append(
key_str.format("m.get_topics()", width,
"Get the most probable words per topic."))
extra.append(
key_str.format("m.predict(new_docs)", width,
"Make predictions for new documents."))
return out + '\n' + '\n'.join(extra)
def __repr__(self):
"""
Print a string description of the model, when the model name is entered
in the terminal.
"""
(sections, section_titles) = self._get_summary_struct()
return _toolkit_repr_print(self, sections, section_titles, width=30)
def __repr__(self):
"""
Print a string description of the model when the model name is entered
in the terminal.
"""
width = 40
sections, section_titles = self._get_summary_struct()
out = _tkutl._toolkit_repr_print(self, sections, section_titles, width=width)
return out
def __repr__(self):
"""
Print a string description of the model when the model name is entered
in the terminal.
"""
width = 40
sections, section_titles = self._get_summary_struct()
detector = self.__proxy__['detector']
out = _tkutl._toolkit_repr_print(detector, sections, section_titles,
width=width, class_name='OneShotObjectDetector')
return out
def __repr__(self):
"""
Print a string description of the model when the model name is entered
in the terminal.
"""
import turicreate.toolkits._internal_utils as tkutl
width = 40
sections, section_titles = self._get_summary_struct()
out = tkutl._toolkit_repr_print(self, sections, section_titles, width=width)
return out
def __repr__(self):
descriptions = [(k, _precomputed_field(v)) for k, v in six.iteritems(self._describe_fields())]
(sections, section_titles) = self._get_summary_struct()
non_empty_sections = [s for s in sections if len(s) > 0]
non_empty_section_titles = [section_titles[i] for i in range(len(sections)) if len(sections[i]) > 0]
non_empty_section_titles.append('Queryable Fields')
non_empty_sections.append(descriptions)
return _toolkit_repr_print(self, non_empty_sections, non_empty_section_titles, width=40)
def __repr__(self):
"""
Print a string description of the model when the model name is entered
in the terminal.
"""
width = 40
sections, section_titles = self._get_summary_struct()
accessible_fields = {
"cluster_id": "Cluster label for each row in the input dataset."}
out = _toolkit_repr_print(self, sections, section_titles, width=width)
out2 = _summarize_accessible_fields(accessible_fields, width=width)
return out + "\n" + out2
def __repr__(self):
"""
Return a string description of the model, including a description of
the training data, training statistics, and model hyper-parameters.
Returns
-------
out : string
A description of the model.
"""
(sections, section_titles) = self._get_summary_struct()
return _toolkit_repr_print(self, sections, section_titles, width=30)
def __repr__(self):
"""
Return a string description of the model, including a description of
the training data, training statistics, and model hyper-parameters.
Returns
-------
out : string
A description of the model.
"""
accessible_fields = {
"vocabulary": "The vocabulary of the trimmed input."
}
(sections, section_titles) = self._get_summary_struct()
out = _toolkit_repr_print(self, sections, section_titles, width=30)
out2 = _summarize_accessible_fields(accessible_fields, width=30)
return out + "\n" + out2
def __repr__(self):
"""
Print a string description of the model when the model name is entered
in the terminal.
"""
width = 32
(sections, section_titles) = self._get_summary_struct()
accessible_fields = {
"cluster_id": "An SFrame containing the cluster assignments.",
"cluster_info": "An SFrame containing the cluster centers."}
out = _tkutl._toolkit_repr_print(self, sections, section_titles,
width=width)
out2 = _summarize_accessible_fields(accessible_fields, width=width)
return out + "\n" + out2
def __repr__(self):
"""
Returns a string description of the model, including (where relevant)
the schema of the training data, description of the training data,
training statistics, and model hyperparameters.
Returns
-------
out : string
A description of the model.
"""
width = 40
sections, section_titles = self._get_summary_struct()
out = _tkutl._toolkit_repr_print(self,
sections,
section_titles,
width=width)
return out
def __repr__(self):
(sections, section_titles) = self._get_summary_struct()
return _toolkit_repr_print(self, sections, section_titles, 30)
def __repr__(self):
width = 32
(sections, section_titles) = self._get_summary_struct()
out = _toolkit_repr_print(self, sections, section_titles, width=width)
return out
def __repr__(self):
"""
Return a string description of the transform.
"""
(sections, section_titles) = self._get_summary_struct()
return _toolkit_repr_print(self, sections, section_titles)
