feat(Analysis/InnerProductSpace/TensorProduct): Add TensorProduct.mapL

[TJHeeringa]

---

Analysis/innerProductSpace/TensorProduct has a TODO for a continuous version of TensorProduct.map. One place which contains a proof for this is at stack. #38755 was lemma 1 of that. This PR is the remainder.

AI:
Used to generate exists_repr.

[github-actions]

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[github-actions]

PR summary 0b8bf3008b

Import changes exceeding 2%

%	File
+14.19%	Mathlib.Analysis.InnerProductSpace.TensorProduct

Import changes for modified files

Dependency changes

File	Base Count	Head Count	Change
Mathlib.Analysis.InnerProductSpace.TensorProduct	2177	2486	+309 (+14.19%)

Import changes for all files

Files	Import difference
Mathlib.Analysis.InnerProductSpace.Coalgebra Mathlib.Analysis.InnerProductSpace.TensorProduct	309

---

Declarations diff

+ adjoint_mapL
+ exists_repr
+ mapIdL
+ mapL
+ mapLId
+ mapL_tmul
+ norm_mapIdL
+ norm_mapL
+ norm_mapLId

You can run this locally as follows

## from your `mathlib4` directory:
git clone https://github.com/leanprover-community/mathlib-ci.git ../mathlib-ci

## summary with just the declaration names:
../mathlib-ci/scripts/pr_summary/declarations_diff.sh <optional_commit>

## more verbose report:
../mathlib-ci/scripts/pr_summary/declarations_diff.sh long <optional_commit>

The doc-module for scripts/pr_summary/declarations_diff.sh in the mathlib-ci repository contains some details about this script.

---

No changes to strong technical debt.

No changes to weak technical debt.

Current commit 0b8bf3008b
Reference commit c9883ce29a

This script lives in the mathlib-ci repository. To run it locally, from your mathlib4 directory:

git clone https://github.com/leanprover-community/mathlib-ci.git ../mathlib-ci
../mathlib-ci/scripts/reporting/technical-debt-metrics.sh pr_summary

• The relative value is the weighted sum of the differences with weight given by the inverse of the current value of the statistic.
  • The absolute value is the relative value divided by the total sum of the inverses of the current values (i.e. the weighted average of the differences).