r"""
Use this module to write your answers to the questions in the notebook.

Note: Inside the answer strings you can use Markdown format and also LaTeX
math (delimited with $$).
"""

# ==============
# Part 1 answers


def part1_generation_params():
    start_seq = ""
    temperature = .0001
    # TODO: Tweak the parameters to generate a literary masterpiece.
    # ====== YOUR CODE: ======
    raise NotImplementedError()
    # ========================
    return start_seq, temperature


part1_q1 = r"""
**Your answer:**


Write your answer using **markdown** and $\LaTeX$:
```python
# A code block
a = 2
```
An equation: $e^{i\pi} -1 = 0$

"""

part1_q2 = r"""
**Your answer:**


Write your answer using **markdown** and $\LaTeX$:
```python
# A code block
a = 2
```
An equation: $e^{i\pi} -1 = 0$

"""

part1_q3 = r"""
**Your answer:**


Write your answer using **markdown** and $\LaTeX$:
```python
# A code block
a = 2
```
An equation: $e^{i\pi} -1 = 0$

"""

part1_q4 = r"""
**Your answer:**


Write your answer using **markdown** and $\LaTeX$:
```python
# A code block
a = 2
```
An equation: $e^{i\pi} -1 = 0$

"""
# ==============


# ==============
# Part 2 answers

PART2_CUSTOM_DATA_URL = None


def part2_vae_hyperparams():
    hypers = dict(
        batch_size=0,
        h_dim=0, z_dim=0, x_sigma2=0,
        learn_rate=0.0, betas=(0.0, 0.0),
    )
    # TODO: Tweak the hyperparameters to generate a former president.
    # ====== YOUR CODE: ======
    raise NotImplementedError()
    # ========================
    return hypers


part2_q1 = r"""
**Your answer:**


Write your answer using **markdown** and $\LaTeX$:
```python
# A code block
a = 2
```
An equation: $e^{i\pi} -1 = 0$

"""

# ==============

# ==============
# Part 3 answers

PART3_CUSTOM_DATA_URL = None


def part3_gan_hyperparams():
    hypers = dict(
        batch_size=0, z_dim=0,
        data_label=0, label_noise=0.0,
        discriminator_optimizer=dict(
            type='',  # Any name in nn.optim like SGD, Adam
            lr=0.0,
        ),
        generator_optimizer=dict(
            type='',  # Any name in nn.optim like SGD, Adam
            lr=0.0,
        ),
    )
    # TODO: Tweak the hyperparameters to train your GAN.
    # ====== YOUR CODE: ======
    raise NotImplementedError()
    # ========================
    return hypers


part3_q1 = r"""
**Your answer:**


Write your answer using **markdown** and $\LaTeX$:
```python
# A code block
a = 2
```
An equation: $e^{i\pi} -1 = 0$

"""

part3_q2 = r"""
**Your answer:**


Write your answer using **markdown** and $\LaTeX$:
```python
# A code block
a = 2
```
An equation: $e^{i\pi} -1 = 0$

"""

part3_q3 = r"""
**Your answer:**


Write your answer using **markdown** and $\LaTeX$:
```python
# A code block
a = 2
```
An equation: $e^{i\pi} -1 = 0$

"""

# ==============


