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)