Initial Query

I have list of indexes and I want to convert it to one hot vector using jax and the function should be jittable and the function should be jitted. name the function one_hot and it should get two arguments the first one is the indexes and the second one is the number of possible labeles. Just give me the code

LLM Generation

Query

I have list of indexes and I want to convert it to one hot vector using jax and the function should be jittable and the function should be jitted. name the function one_hot and it should get two arguments the first one is the indexes and the second one is the number of possible labeles. Just give me the code

Output

import jax import jax.numpy as jnp @jax.jit def one_hot(indexes, num_labels): return jnp.array(indexes[:, None] == jnp.arange(num_labels), dtype=jnp.int32) # Example usage indexes = jnp.array([1, 0, 2, 1]) num_labels = 3 one_hot_vector = one_hot(indexes, num_labels) print(one_hot_vector)

Extract Code

I extracted the following code from that output: 

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import jax
import jax.numpy as jnp

@jax.jit
def one_hot(indexes, num_labels):
    return jnp.array(indexes[:, None] == jnp.arange(num_labels), dtype=jnp.int32)

Run Code Interpreter

Running the following program: 

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import jax
import jax.numpy as jnp

@jax.jit
def one_hot(indexes, num_labels):
    return jnp.array(indexes[:, None] == jnp.arange(num_labels), dtype=jnp.int32)


import jax.numpy as jnp

answer = str(one_hot(jnp.array([1,2,0]),5))
expected = str(jnp.array([[0.0,1.0,0.0,0.0,0.0],[0.0,0.0,1.0,0.0,0.0],[1.0,0.0,0.0,0.0,0.0]]))
assert answer == expected, f'Wrong answer; got {answer} instead of {expected}'
print('All tests passed')
And got the output: 
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Traceback (most recent call last):
  File "/usr/src/app/main.py", line 11, in <module>
    answer = str(one_hot(jnp.array([1,2,0]),5))
                 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/usr/src/app/main.py", line 6, in one_hot
    return jnp.array(indexes[:, None] == jnp.arange(num_labels), dtype=jnp.int32)
                                         ^^^^^^^^^^^^^^^^^^^^^^
  File "/usr/local/lib/python3.11/dist-packages/jax/_src/numpy/lax_numpy.py", line 2490, in arange
    start = core.concrete_or_error(None, start, "It arose in the jnp.arange argument 'stop'")
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
jax.errors.ConcretizationTypeError: Abstract tracer value encountered where concrete value is expected: traced array with shape int32[].
It arose in the jnp.arange argument 'stop'
The error occurred while tracing the function one_hot at /usr/src/app/main.py:4 for jit. This concrete value was not available in Python because it depends on the value of the argument num_labels.
See https://jax.readthedocs.io/en/latest/errors.html#jax.errors.ConcretizationTypeError</p>
<hr />
<p>For simplicity, JAX has removed its internal frames from the traceback of the following exception. Set JAX_TRACEBACK_FILTERING=off to include these.

Substring Evaluation

Testing if the previous output contains the string All tests passed: False

Initial Query

I have list of indexes and I want to convert it to one hot vector using jax and the function should be jittable and the function should be jitted. name the function one_hot and it should get two arguments the first one is the indexes and the second one is the number of possible labeles. Just give me the code

LLM Generation

Query

I have list of indexes and I want to convert it to one hot vector using jax and the function should be jittable and the function should be jitted. name the function one_hot and it should get two arguments the first one is the indexes and the second one is the number of possible labeles. Just give me the code

Output

import jax import jax.numpy as jnp @jax.jit def one_hot(indexes, num_labels): return jnp.array(indexes[:, None] == jnp.arange(num_labels), dtype=int) # Example usage indexes = jnp.array([1, 2, 0]) num_labels = 3 one_hot_vector = one_hot(indexes, num_labels) print(one_hot_vector)

Extract Code

I extracted the following code from that output: 

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import jax
import jax.numpy as jnp

@jax.jit
def one_hot(indexes, num_labels):
    return jnp.array(indexes[:, None] == jnp.arange(num_labels), dtype=int)

Run Code Interpreter

Running the following program: 

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import jax
import jax.numpy as jnp

@jax.jit
def one_hot(indexes, num_labels):
    return jnp.array(indexes[:, None] == jnp.arange(num_labels), dtype=int)


import jax.numpy as jnp

answer = str(one_hot(jnp.array([1,2,0]),5))
expected = str(jnp.array([[0.0,1.0,0.0,0.0,0.0],[0.0,0.0,1.0,0.0,0.0],[1.0,0.0,0.0,0.0,0.0]]))
assert answer == expected, f'Wrong answer; got {answer} instead of {expected}'
print('All tests passed')
And got the output: 
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Traceback (most recent call last):
  File "/usr/src/app/main.py", line 11, in <module>
    answer = str(one_hot(jnp.array([1,2,0]),5))
                 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/usr/src/app/main.py", line 6, in one_hot
    return jnp.array(indexes[:, None] == jnp.arange(num_labels), dtype=int)
                                         ^^^^^^^^^^^^^^^^^^^^^^
  File "/usr/local/lib/python3.11/dist-packages/jax/_src/numpy/lax_numpy.py", line 2490, in arange
    start = core.concrete_or_error(None, start, "It arose in the jnp.arange argument 'stop'")
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
jax.errors.ConcretizationTypeError: Abstract tracer value encountered where concrete value is expected: traced array with shape int32[].
It arose in the jnp.arange argument 'stop'
The error occurred while tracing the function one_hot at /usr/src/app/main.py:4 for jit. This concrete value was not available in Python because it depends on the value of the argument num_labels.
See https://jax.readthedocs.io/en/latest/errors.html#jax.errors.ConcretizationTypeError</p>
<hr />
<p>For simplicity, JAX has removed its internal frames from the traceback of the following exception. Set JAX_TRACEBACK_FILTERING=off to include these.

Substring Evaluation

Testing if the previous output contains the string All tests passed: False

Initial Query

I have list of indexes and I want to convert it to one hot vector using jax and the function should be jittable and the function should be jitted. name the function one_hot and it should get two arguments the first one is the indexes and the second one is the number of possible labeles. Just give me the code

LLM Generation

Query

I have list of indexes and I want to convert it to one hot vector using jax and the function should be jittable and the function should be jitted. name the function one_hot and it should get two arguments the first one is the indexes and the second one is the number of possible labeles. Just give me the code

Output

import jax import jax.numpy as jnp @jax.jit def one_hot(indexes, num_labels): return jnp.array(indexes[:, None] == jnp.arange(num_labels), dtype=jnp.int32) # Example Usage indexes = jnp.array([0, 2, 1, 0]) num_labels = 3 one_hot_vector = one_hot(indexes, num_labels) print(one_hot_vector)

Extract Code

I extracted the following code from that output: 

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import jax
import jax.numpy as jnp

@jax.jit
def one_hot(indexes, num_labels):
    return jnp.array(indexes[:, None] == jnp.arange(num_labels), dtype=jnp.int32)

Run Code Interpreter

Running the following program: 

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import jax
import jax.numpy as jnp

@jax.jit
def one_hot(indexes, num_labels):
    return jnp.array(indexes[:, None] == jnp.arange(num_labels), dtype=jnp.int32)


import jax.numpy as jnp

answer = str(one_hot(jnp.array([1,2,0]),5))
expected = str(jnp.array([[0.0,1.0,0.0,0.0,0.0],[0.0,0.0,1.0,0.0,0.0],[1.0,0.0,0.0,0.0,0.0]]))
assert answer == expected, f'Wrong answer; got {answer} instead of {expected}'
print('All tests passed')
And got the output: 
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Traceback (most recent call last):
  File "/usr/src/app/main.py", line 11, in <module>
    answer = str(one_hot(jnp.array([1,2,0]),5))
                 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/usr/src/app/main.py", line 6, in one_hot
    return jnp.array(indexes[:, None] == jnp.arange(num_labels), dtype=jnp.int32)
                                         ^^^^^^^^^^^^^^^^^^^^^^
  File "/usr/local/lib/python3.11/dist-packages/jax/_src/numpy/lax_numpy.py", line 2490, in arange
    start = core.concrete_or_error(None, start, "It arose in the jnp.arange argument 'stop'")
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
jax.errors.ConcretizationTypeError: Abstract tracer value encountered where concrete value is expected: traced array with shape int32[].
It arose in the jnp.arange argument 'stop'
The error occurred while tracing the function one_hot at /usr/src/app/main.py:4 for jit. This concrete value was not available in Python because it depends on the value of the argument num_labels.
See https://jax.readthedocs.io/en/latest/errors.html#jax.errors.ConcretizationTypeError</p>
<hr />
<p>For simplicity, JAX has removed its internal frames from the traceback of the following exception. Set JAX_TRACEBACK_FILTERING=off to include these.

Substring Evaluation

Testing if the previous output contains the string All tests passed: False

Initial Query

I have list of indexes and I want to convert it to one hot vector using jax and the function should be jittable and the function should be jitted. name the function one_hot and it should get two arguments the first one is the indexes and the second one is the number of possible labeles. Just give me the code

LLM Generation

Query

I have list of indexes and I want to convert it to one hot vector using jax and the function should be jittable and the function should be jitted. name the function one_hot and it should get two arguments the first one is the indexes and the second one is the number of possible labeles. Just give me the code

Output

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import jax.numpy as jnp
from jax import jit

@jit
def one_hot(indexes, num_labels):
    return jnp.array(indexes[:, None] == jnp.arange(num_labels), dtype=jnp.float32)

# Example usage
indexes = jnp.array([1, 0, 2, 1])
num_labels = 3
one_hot_vector = one_hot(indexes, num_labels)
print(one_hot_vector)

Extract Code

I extracted the following code from that output: 

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import jax.numpy as jnp
from jax import jit

@jit
def one_hot(indexes, num_labels):
    return jnp.array(indexes[:, None] == jnp.arange(num_labels), dtype=jnp.float32)

# Example usage
indexes = jnp.array([1, 0, 2, 1])
num_labels = 3
one_hot_vector = one_hot(indexes, num_labels)
print(one_hot_vector)

Run Code Interpreter

Running the following program: 

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import jax.numpy as jnp
from jax import jit

@jit
def one_hot(indexes, num_labels):
    return jnp.array(indexes[:, None] == jnp.arange(num_labels), dtype=jnp.float32)

# Example usage
indexes = jnp.array([1, 0, 2, 1])
num_labels = 3
one_hot_vector = one_hot(indexes, num_labels)
print(one_hot_vector)



import jax.numpy as jnp

answer = str(one_hot(jnp.array([1,2,0]),5))
expected = str(jnp.array([[0.0,1.0,0.0,0.0,0.0],[0.0,0.0,1.0,0.0,0.0],[1.0,0.0,0.0,0.0,0.0]]))
assert answer == expected, f'Wrong answer; got {answer} instead of {expected}'
print('All tests passed')
And got the output: 
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Traceback (most recent call last):
  File "/usr/src/app/main.py", line 12, in <module>
    one_hot_vector = one_hot(indexes, num_labels)
                     ^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/usr/src/app/main.py", line 7, in one_hot
    return jnp.array(indexes[:, None] == jnp.arange(num_labels), dtype=jnp.float32)
                                         ^^^^^^^^^^^^^^^^^^^^^^
  File "/usr/local/lib/python3.11/dist-packages/jax/_src/numpy/lax_numpy.py", line 2490, in arange
    start = core.concrete_or_error(None, start, "It arose in the jnp.arange argument 'stop'")
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
jax.errors.ConcretizationTypeError: Abstract tracer value encountered where concrete value is expected: traced array with shape int32[].
It arose in the jnp.arange argument 'stop'
The error occurred while tracing the function one_hot at /usr/src/app/main.py:5 for jit. This concrete value was not available in Python because it depends on the value of the argument num_labels.
See https://jax.readthedocs.io/en/latest/errors.html#jax.errors.ConcretizationTypeError</p>
<hr />
<p>For simplicity, JAX has removed its internal frames from the traceback of the following exception. Set JAX_TRACEBACK_FILTERING=off to include these.

Substring Evaluation

Testing if the previous output contains the string All tests passed: False

Initial Query

I have list of indexes and I want to convert it to one hot vector using jax and the function should be jittable and the function should be jitted. name the function one_hot and it should get two arguments the first one is the indexes and the second one is the number of possible labeles. Just give me the code

LLM Generation

Query

I have list of indexes and I want to convert it to one hot vector using jax and the function should be jittable and the function should be jitted. name the function one_hot and it should get two arguments the first one is the indexes and the second one is the number of possible labeles. Just give me the code

Output

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import jax
import jax.numpy as jnp

@jax.jit
def one_hot(indexes, num_labels):
    return jnp.array(indexes[:, None] == jnp.arange(num_labels), dtype=jnp.int32)

# Example usage
indexes = jnp.array([1, 0, 2])
num_labels = 3
one_hot_vector = one_hot(indexes, num_labels)
print(one_hot_vector)

Extract Code

I extracted the following code from that output: 

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import jax
import jax.numpy as jnp

@jax.jit
def one_hot(indexes, num_labels):
    return jnp.array(indexes[:, None] == jnp.arange(num_labels), dtype=jnp.int32)

# Example usage
indexes = jnp.array([1, 0, 2])
num_labels = 3
one_hot_vector = one_hot(indexes, num_labels)
print(one_hot_vector)

Run Code Interpreter

Running the following program: 

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import jax
import jax.numpy as jnp

@jax.jit
def one_hot(indexes, num_labels):
    return jnp.array(indexes[:, None] == jnp.arange(num_labels), dtype=jnp.int32)

# Example usage
indexes = jnp.array([1, 0, 2])
num_labels = 3
one_hot_vector = one_hot(indexes, num_labels)
print(one_hot_vector)



import jax.numpy as jnp

answer = str(one_hot(jnp.array([1,2,0]),5))
expected = str(jnp.array([[0.0,1.0,0.0,0.0,0.0],[0.0,0.0,1.0,0.0,0.0],[1.0,0.0,0.0,0.0,0.0]]))
assert answer == expected, f'Wrong answer; got {answer} instead of {expected}'
print('All tests passed')
And got the output: 
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Traceback (most recent call last):
  File "/usr/src/app/main.py", line 12, in <module>
    one_hot_vector = one_hot(indexes, num_labels)
                     ^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/usr/src/app/main.py", line 7, in one_hot
    return jnp.array(indexes[:, None] == jnp.arange(num_labels), dtype=jnp.int32)
                                         ^^^^^^^^^^^^^^^^^^^^^^
  File "/usr/local/lib/python3.11/dist-packages/jax/_src/numpy/lax_numpy.py", line 2490, in arange
    start = core.concrete_or_error(None, start, "It arose in the jnp.arange argument 'stop'")
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
jax.errors.ConcretizationTypeError: Abstract tracer value encountered where concrete value is expected: traced array with shape int32[].
It arose in the jnp.arange argument 'stop'
The error occurred while tracing the function one_hot at /usr/src/app/main.py:5 for jit. This concrete value was not available in Python because it depends on the value of the argument num_labels.
See https://jax.readthedocs.io/en/latest/errors.html#jax.errors.ConcretizationTypeError</p>
<hr />
<p>For simplicity, JAX has removed its internal frames from the traceback of the following exception. Set JAX_TRACEBACK_FILTERING=off to include these.

Substring Evaluation

Testing if the previous output contains the string All tests passed: False