Return a function that executes 'f'. In TF 2.x, this is the same as `f`. In TF 1.x, returns a Python function that executes the graph defined by `f` in a Session. Args: f: the function. xs_dtypes: dtypes of f's arguments. Returns: a function that will be evaluated in b
(f, xs_dtypes)
| 95 | |
| 96 | |
| 97 | def _prepare(f, xs_dtypes): |
| 98 | """Return a function that executes 'f'. |
| 99 | |
| 100 | In TF 2.x, this is the same as `f`. |
| 101 | In TF 1.x, returns a Python function that executes the graph defined by `f` |
| 102 | in a Session. |
| 103 | |
| 104 | Args: |
| 105 | f: the function. |
| 106 | xs_dtypes: dtypes of f's arguments. |
| 107 | |
| 108 | Returns: |
| 109 | a function that will be evaluated in both graph and eager mode |
| 110 | """ |
| 111 | if context.executing_eagerly(): |
| 112 | |
| 113 | def decorated_eager(*xs_data): |
| 114 | return f(*map(ops.convert_to_tensor, xs_data)) |
| 115 | |
| 116 | return decorated_eager |
| 117 | xs = [array_ops.placeholder(x_dtype) for x_dtype in xs_dtypes] |
| 118 | y = f(*xs) |
| 119 | sess = ops.get_default_session() |
| 120 | def decorated_graph(*xs_data): |
| 121 | xs_data = [_to_numpy(a) for a in xs_data] |
| 122 | return sess.run(y, feed_dict=dict(zip(xs, xs_data))) |
| 123 | return decorated_graph |
| 124 | |
| 125 | |
| 126 | def _compute_theoretical_jacobian(f, y_shape, y_dtype, xs, param): |
no test coverage detected