1path: "tensorflow.keras.metrics"
2tf_module {
3  member {
4    name: "AUC"
5    mtype: "<type \'type\'>"
6  }
7  member {
8    name: "Accuracy"
9    mtype: "<type \'type\'>"
10  }
11  member {
12    name: "BinaryAccuracy"
13    mtype: "<type \'type\'>"
14  }
15  member {
16    name: "BinaryCrossentropy"
17    mtype: "<type \'type\'>"
18  }
19  member {
20    name: "CategoricalAccuracy"
21    mtype: "<type \'type\'>"
22  }
23  member {
24    name: "CategoricalCrossentropy"
25    mtype: "<type \'type\'>"
26  }
27  member {
28    name: "CategoricalHinge"
29    mtype: "<type \'type\'>"
30  }
31  member {
32    name: "CosineSimilarity"
33    mtype: "<type \'type\'>"
34  }
35  member {
36    name: "FalseNegatives"
37    mtype: "<type \'type\'>"
38  }
39  member {
40    name: "FalsePositives"
41    mtype: "<type \'type\'>"
42  }
43  member {
44    name: "Hinge"
45    mtype: "<type \'type\'>"
46  }
47  member {
48    name: "KLDivergence"
49    mtype: "<type \'type\'>"
50  }
51  member {
52    name: "LogCoshError"
53    mtype: "<type \'type\'>"
54  }
55  member {
56    name: "Mean"
57    mtype: "<type \'type\'>"
58  }
59  member {
60    name: "MeanAbsoluteError"
61    mtype: "<type \'type\'>"
62  }
63  member {
64    name: "MeanAbsolutePercentageError"
65    mtype: "<type \'type\'>"
66  }
67  member {
68    name: "MeanIoU"
69    mtype: "<type \'type\'>"
70  }
71  member {
72    name: "MeanRelativeError"
73    mtype: "<type \'type\'>"
74  }
75  member {
76    name: "MeanSquaredError"
77    mtype: "<type \'type\'>"
78  }
79  member {
80    name: "MeanSquaredLogarithmicError"
81    mtype: "<type \'type\'>"
82  }
83  member {
84    name: "MeanTensor"
85    mtype: "<type \'type\'>"
86  }
87  member {
88    name: "Metric"
89    mtype: "<type \'type\'>"
90  }
91  member {
92    name: "Poisson"
93    mtype: "<type \'type\'>"
94  }
95  member {
96    name: "Precision"
97    mtype: "<type \'type\'>"
98  }
99  member {
100    name: "Recall"
101    mtype: "<type \'type\'>"
102  }
103  member {
104    name: "RootMeanSquaredError"
105    mtype: "<type \'type\'>"
106  }
107  member {
108    name: "SensitivityAtSpecificity"
109    mtype: "<type \'type\'>"
110  }
111  member {
112    name: "SparseCategoricalAccuracy"
113    mtype: "<type \'type\'>"
114  }
115  member {
116    name: "SparseCategoricalCrossentropy"
117    mtype: "<type \'type\'>"
118  }
119  member {
120    name: "SparseTopKCategoricalAccuracy"
121    mtype: "<type \'type\'>"
122  }
123  member {
124    name: "SpecificityAtSensitivity"
125    mtype: "<type \'type\'>"
126  }
127  member {
128    name: "SquaredHinge"
129    mtype: "<type \'type\'>"
130  }
131  member {
132    name: "Sum"
133    mtype: "<type \'type\'>"
134  }
135  member {
136    name: "TopKCategoricalAccuracy"
137    mtype: "<type \'type\'>"
138  }
139  member {
140    name: "TrueNegatives"
141    mtype: "<type \'type\'>"
142  }
143  member {
144    name: "TruePositives"
145    mtype: "<type \'type\'>"
146  }
147  member_method {
148    name: "KLD"
149    argspec: "args=[\'y_true\', \'y_pred\'], varargs=None, keywords=None, defaults=None"
150  }
151  member_method {
152    name: "MAE"
153    argspec: "args=[\'y_true\', \'y_pred\'], varargs=None, keywords=None, defaults=None"
154  }
155  member_method {
156    name: "MAPE"
157    argspec: "args=[\'y_true\', \'y_pred\'], varargs=None, keywords=None, defaults=None"
158  }
159  member_method {
160    name: "MSE"
161    argspec: "args=[\'y_true\', \'y_pred\'], varargs=None, keywords=None, defaults=None"
162  }
163  member_method {
164    name: "MSLE"
165    argspec: "args=[\'y_true\', \'y_pred\'], varargs=None, keywords=None, defaults=None"
166  }
167  member_method {
168    name: "binary_accuracy"
169    argspec: "args=[\'y_true\', \'y_pred\', \'threshold\'], varargs=None, keywords=None, defaults=[\'0.5\'], "
170  }
171  member_method {
172    name: "binary_crossentropy"
173    argspec: "args=[\'y_true\', \'y_pred\', \'from_logits\', \'label_smoothing\'], varargs=None, keywords=None, defaults=[\'False\', \'0\'], "
174  }
175  member_method {
176    name: "categorical_accuracy"
177    argspec: "args=[\'y_true\', \'y_pred\'], varargs=None, keywords=None, defaults=None"
178  }
179  member_method {
180    name: "categorical_crossentropy"
181    argspec: "args=[\'y_true\', \'y_pred\', \'from_logits\', \'label_smoothing\'], varargs=None, keywords=None, defaults=[\'False\', \'0\'], "
182  }
183  member_method {
184    name: "cosine"
185    argspec: "args=[\'y_true\', \'y_pred\', \'axis\'], varargs=None, keywords=None, defaults=[\'-1\'], "
186  }
187  member_method {
188    name: "cosine_proximity"
189    argspec: "args=[\'y_true\', \'y_pred\', \'axis\'], varargs=None, keywords=None, defaults=[\'-1\'], "
190  }
191  member_method {
192    name: "deserialize"
193    argspec: "args=[\'config\', \'custom_objects\'], varargs=None, keywords=None, defaults=[\'None\'], "
194  }
195  member_method {
196    name: "get"
197    argspec: "args=[\'identifier\'], varargs=None, keywords=None, defaults=None"
198  }
199  member_method {
200    name: "hinge"
201    argspec: "args=[\'y_true\', \'y_pred\'], varargs=None, keywords=None, defaults=None"
202  }
203  member_method {
204    name: "kld"
205    argspec: "args=[\'y_true\', \'y_pred\'], varargs=None, keywords=None, defaults=None"
206  }
207  member_method {
208    name: "kullback_leibler_divergence"
209    argspec: "args=[\'y_true\', \'y_pred\'], varargs=None, keywords=None, defaults=None"
210  }
211  member_method {
212    name: "mae"
213    argspec: "args=[\'y_true\', \'y_pred\'], varargs=None, keywords=None, defaults=None"
214  }
215  member_method {
216    name: "mape"
217    argspec: "args=[\'y_true\', \'y_pred\'], varargs=None, keywords=None, defaults=None"
218  }
219  member_method {
220    name: "mean_absolute_error"
221    argspec: "args=[\'y_true\', \'y_pred\'], varargs=None, keywords=None, defaults=None"
222  }
223  member_method {
224    name: "mean_absolute_percentage_error"
225    argspec: "args=[\'y_true\', \'y_pred\'], varargs=None, keywords=None, defaults=None"
226  }
227  member_method {
228    name: "mean_squared_error"
229    argspec: "args=[\'y_true\', \'y_pred\'], varargs=None, keywords=None, defaults=None"
230  }
231  member_method {
232    name: "mean_squared_logarithmic_error"
233    argspec: "args=[\'y_true\', \'y_pred\'], varargs=None, keywords=None, defaults=None"
234  }
235  member_method {
236    name: "mse"
237    argspec: "args=[\'y_true\', \'y_pred\'], varargs=None, keywords=None, defaults=None"
238  }
239  member_method {
240    name: "msle"
241    argspec: "args=[\'y_true\', \'y_pred\'], varargs=None, keywords=None, defaults=None"
242  }
243  member_method {
244    name: "poisson"
245    argspec: "args=[\'y_true\', \'y_pred\'], varargs=None, keywords=None, defaults=None"
246  }
247  member_method {
248    name: "serialize"
249    argspec: "args=[\'metric\'], varargs=None, keywords=None, defaults=None"
250  }
251  member_method {
252    name: "sparse_categorical_accuracy"
253    argspec: "args=[\'y_true\', \'y_pred\'], varargs=None, keywords=None, defaults=None"
254  }
255  member_method {
256    name: "sparse_categorical_crossentropy"
257    argspec: "args=[\'y_true\', \'y_pred\', \'from_logits\', \'axis\'], varargs=None, keywords=None, defaults=[\'False\', \'-1\'], "
258  }
259  member_method {
260    name: "sparse_top_k_categorical_accuracy"
261    argspec: "args=[\'y_true\', \'y_pred\', \'k\'], varargs=None, keywords=None, defaults=[\'5\'], "
262  }
263  member_method {
264    name: "squared_hinge"
265    argspec: "args=[\'y_true\', \'y_pred\'], varargs=None, keywords=None, defaults=None"
266  }
267  member_method {
268    name: "top_k_categorical_accuracy"
269    argspec: "args=[\'y_true\', \'y_pred\', \'k\'], varargs=None, keywords=None, defaults=[\'5\'], "
270  }
271}
272