| test | |
| dfgsdgfdsg | |
| dfs | |
| gdf | |
| sg | |
| dsfg |
🐟 Cervo's Cute, cool, classy. Every dish was an absolute hit. Primarily seafood, but non-seafood dishes are on par. Hard to get into with anything more than 2 people.
🇹🇭 Thai Diner A revelation. Somehow has a ton of fun while keeping the food top notch. The breakfast sandwich is great, but fair warning: you'll be eyeing the dinner dishes.
🍲 Wu's Wonton King
| ffadce40-ace0-4547-b248-baf8bf6fa1cf | |
| f0154557-bdb7-4c3c-b479-6ea2852a5cac |
| ffadce40-ace0-4547-b248-baf8bf6fa1cf | f0154557-bdb7-4c3c-b479-6ea2852a5cac |
|---|
| extend type Query { | |
| __schema: __Schema! | |
| __type(name: String!): __Type | |
| } | |
| type __Schema { | |
| description: String | |
| types: [__Type!]! | |
| queryType: __Type! | |
| mutationType: __Type |
| import { | |
| GraphQLBoolean, | |
| GraphQLError, | |
| GraphQLList, | |
| GraphQLNonNull, | |
| GraphQLString | |
| } from 'graphql'; | |
| import { | |
| fromGlobalId, |
| preds, targs = learn.get_preds() | |
| x_val = x[valid_idx]; | |
| y_val = np.array(targs); | |
| y_hat = np.array(preds.flatten()) | |
| plt.plot(x_val, y_val, 'go', label = 'tagets', alpha = .5) | |
| plt.plot(x_val, y_hat, 'ro', label = 'preds', alpha = .5) | |
| plt.legend() | |
| plt.show() |
| model = TabularModel(emb_szs={}, n_cont=1, out_sz=1, layers=[10]); | |
| print(model) |
| learn = Learner(data, model); |
